When I See U Again Lyric
Weastward analyzed 127,183 Airbnb invitee complaints to find out which problems are most likely to be complained almost via Twitter. We reviewed all mentions and replies of @Airbnb, @Airbnb_uk, @AirbnbHelp, etc.
I conceived the original study method in early 2019 and before long thereafter began a collaboration with researchers from John Jay Higher of Criminal Justice and the University of Colorado School of Public Diplomacy in Colorado Springs. The ii.5-year project was funded by ASIS International (the globe's largest membership organization for security management professionals) and via a grant from John Jay Higher.
This 2021 Airbnb research is a follow-upwardly to my 2017 report, "Is Airbnb Safe?" which was inspired by my own Airbnb nightmares in Paris with my wife and baby.
Below is a summary of our key findings and further down the folio we list the cities with the most Airbnb complaints.
Delight note: If you'd like to be the first to know when we update this study or when we publish new research, subscribe Hither ➜
Section ane
Our Methodology
In this academic research, we set out to understand 1 uncomplicated question, "which Airbnb invitee bug are almost probable to exist complained about via Twitter?". Nosotros used a combination of human coding of individual Airbnb Twitter complaints, car learning, and natural language processing techniques to accelerate the categorization and understanding of such a big dataset of 365,250 individual tweets or 169,023 Twitter conversations. Of the 169,023 conversations, 127,183 were from guests reporting their problems.
We had two coders homo-review and categorize a total of v,278 tweets without seeing how the other coder was categorizing each conversation. This allowed us to measure intercoder reliability and we somewhen reached 100% reliability by reviewing and correcting all the tweets they did non agree on. Using this "aureate standard" dataset we were able to then train our custom-built machine learning organization to review the remaining 160,000+ conversations. After several iterations and by employing dissimilar natural linguistic communication processing techniques, we achieved an F1-score ranging from 0.72 to 0.86 beyond all categories.
Read Our Full Detailed Methodology (Click to expand)
Notation: the methodology shared below was initially described by Binns and Kempf (2020) in their report for ASIS which is titled, "Using Social Media to Get together Security Intelligence" and is quoted or paraphrased here.
Obtaining the information
All tweets used in this report are publicly available on the Twitter platform at the time of publishing and mentioned one or more of the post-obit Twitter accounts: @AirbnbHelp, @Airbnb, @Airbnb_uk, etc. In order to speed up the review procedure, we used the paid Twitter developer API for bulk downloads of all the tweets shared by Airbnb users. Nosotros were able to download 365,250 individual tweets which gave us a total of 169,023 conversations dating from January 1st, 2015 through to September 2d, 2020.
Unit of analysis
In this research, the unit of measurement of analysis is a Twitter conversation. Each conversation may comprise several individual posts by Twitter users (tweets), including the original tweet and responses unremarkably from @AirbnbHelp. For simplicity, "tweet" and "chat" are interchangeable.
Human Coding and Intercoder Reliability
In this context, coding means "categorizing" or labeling the tweets into predetermined categories. Using humans to code an initial batch of over 3,000 tweets gave usa a way to systematically categorize the data with a loftier level of accuracy. In this case, Twitter conversations were coded in ii stages. First, information technology was determined whether the initial tweet was from an Airbnb invitee, host, or a neighbor/citizen. We also used a fourth category, "unknown," which was used when the coder was not able to identify the person tweeting. This categorization was washed in order to be able to identify the unique vulnerabilities of the primary parties tweeting, primarily, Airbnb guests vs. Airbnb hosts.
The 2nd footstep was to identify the nature of the problem. Categories of unlike types of issues were developed through brainstorming based on my previous Airbnb report, a review of prominent media coverage related to issues nearly Airbnb, researchers' personal experiences, and the types of situations that were commonly found when reviewing a preliminary set up of 300 random conversations.
To ensure intercoder reliability, i.eastward., that coders were analyzing conversations similarly, two coders analyzed the same ready of data separately without knowing how the other coder was categorizing each conversation. This coding was performed on a web app platform designed by the motorcar learning visitor Sciling, the AI contractor for this project. Each coder initially categorized a randomized sample of 300 conversations or about 0.2% of the total 169,023 Twitter conversations about Airbnb. Coders identified the type of tweeter and and so assigned up to three categories of types of complaints to each conversation.
The platform allowed for a comparison of the coders' work to identify the extent to which the coders agreed. Considering intercoder reliability is essential for this process, the coders and researchers closely examined the conversations that the coders did not agree on. As a group, researchers and coders came to a consensus every bit to the accurate coding and amended the coding definitions every bit needed. With new clarity, the coders coded another set of 300-500 conversations. This process was repeated until intercoder reliability was 75%. Finally, the researchers reviewed the remaining conversations that the coders had disagreed on to resolve the disharmonize and accomplish intercoder reliability of 100%. In total, 3,616 conversations, or 2.14%, had been coded manually.
Machine learning
A majority of the human-coded conversations were introduced to the reckoner with the intent that it would learn patterns from the coded conversations and categorize the remaining conversations using Natural Language Processing. These computer-coded conversations were then compared to the remaining human-coded conversations to summate a level of accurateness. Sciling reported that their staff used multiple models to train the machine to recognize patterns in the human being coding, including addressing the data imbalance between tweets from guests versus the other categories.
The following definitions are important:
● Remember "quantifies the number of positive form predictions made out of all positive examples in the dataset" (Brownlee, 2020). From all guest conversations, the machine was able to correctly classify 87%.
● Precision "quantifies the number of positive course predictions that really belong to the positive class" (Brownlee, 2020). From all the conversations that the machine labeled as "guest," 90% were correct.
● F1 Score (or F-measure) is "a measure of the examination'south accuracy and is defined as the weighted harmonic mean of the precision and recall of the test" (Metacademy, n.d.). The F1 score is calculated past dividing the number of observations past the reciprocal of each number in the series, i.e., the precision and recollect of the test.
The figurer was nearly accurate when coding the guests' tweets, as compared to the other types of tweeters, which is likely due to the larger number of tweets to analyze proportionately. Based on the results, it was clear that there were non plenty coded tweets in categories other than "invitee" to train the machine. Due to this, forth with the fact that guests are the primary users of Airbnb, we decided not to do additional coding for "hosts," "citizens," and "other," but rather to focus on the problems that guests feel on Airbnb at this fourth dimension.
The next stride Sciling staff took was to railroad train the car, in multiple iterations, to recognize both who tweeted (specifically, to identify guests) and the type of complaint they offered. With these initial results, we found the F1 score did not reach 80% for nearly of the categories of complaint type, thereby, making the machine's categorization unreliable, which required additional steps, including merging similar categories and reviewing a sample of machine coding.
2 categories of invitee complaints, "business relationship hacking" and "discrimination", met the 80% accuracy threshold that we were striving for. Account hacking received an F1 score of 0.86, and discrimination had an F1 score of 0.81, which means that the accuracy of the machine learning categorization will be higher than 80%. In addition, three other categories had 72% accuracy or higher. These categories included the combined category of client service, locked account and tech issue (F1 score = 0.72), the combined category of host cancels stay/host does not show up (F1 score = 0.78). Equally increased accuracy was unlikely, we adamant these results with more than than 70% accuracy, would exist sufficient for analysis.
Keyword searches
Using the motorcar learning results, the same platform created past Sciling was used to practise keyword research within the machine-coded categories, or in the data gear up every bit a whole, to identify more than granular data about problems facing Airbnb users. Specifically, the AI platform enabled the database of 169,023 Twitter conversations well-nigh Airbnb to exist searched for unmarried words or combinations of words. And then the conversations containing the keywords were analyzed in-depth to gain a better understanding of the context in which they were used by the tweeter.
The methodology for conducting the keyword inquiry was as follows. An initial listing of keywords was curated, designed to recall bug impacting different guest concerns such every bit scams, prophylactic, and security. Some keywords were gleaned from security literature and others had been observed in the tweets reviewed by coders and researchers. For instance, 2 keywords searched for were "burglary" and "theft."
If any keyword retrieved a small number of conversations, defined every bit 275 or less, the conversations were analyzed qualitatively to determine if the chat identified a major issue for Airbnb guests. For instance, a conversation including the give-and-take "attack" might depict a physical assault that occurred at an Airbnb property, which is an obvious security issue. On the other mitt, another conversation might complain about an air freshener existence an "assault on the senses," which is not on the same level of problem.
If there were more than 275 conversations, they were farther refined using advanced keyword searches with a combination of keywords. From the machine learning results and the keyword searches, further findings were developed.
Limitations
The study population was limited to people who have self-reported problems about using Airbnb via Twitter. This fact had several implications for the assay. Start, it excluded any people who are not using Twitter. Thus, findings could not be extrapolated to the entire population of people who employ Airbnb. Second, this population was skewed towards people having complaints as opposed to providing compliments. Tweets to @AirbnbHelp specifically were found to be more than likely negative, considering the tweeters were looking for assistance with a problem that they had failed to go resolution via other means such every bit email or phone advice with Airbnb. Finally, Twitter does not validate the content of tweets, and therefore, some of the conversations might exist untrue or fake. Nevertheless, these limitations did not negate the value of the findings in terms of identifying actionable condom and security issues present on the Airbnb platform. In fact, some of these limitations may take resulted in a population of data that was more than narrowly targeted towards the objective of this study which was to sympathise "which Airbnb guest problems are most probable to be complained about via Twitter?".
My key research partners were:
- Chelsea Binns Ph.D. who is an Assistant Professor in the Department of Security, Burn, and Emergency Management at John Jay College of Criminal Justice. She is an practiced in security & investigations, having previously worked in this capacity for the Metropolis and Country of New York and in the fiscal industry. She is also a licensed Private Investigator and a Certified Fraud Examiner. Chelsea has published 3 books and conducted studies for leading organizations such equally ASIS.
- Robin Kempf JD, Ph.D. who is an Assistant Professor at the University of Colorado School of Public Diplomacy in Colorado Springs. Prior to joining academia, she spent more than than ten years working for the state of Kansas every bit an chaser in a variety of contexts, including Kansas Supreme Court clerk. She has also published numerous manufactures in peer-reviewed journals.
- Germán Sanchis Ph.D. who has a Doctorate caste in Informatics with more 15 years of experience in natural language processing and machine learning, both in bookish enquiry and industrial applications. He is the author of more than 40 publications in international journals and conferences, a fellow member of the committee in many top-level artificial intelligence conferences, and he has also been co-managing director of several Ph.D. theses in the field of tongue processing. Currently, he is CEO of Sciling – the firm that built our automobile learning platform.
- Shea Connors and Julien Roussel who were top students (now graduates) from the criminal justice programs at John Jay Higher and St. John'south University.
- Lastly, this project took more than than two.5 years to complete and involved more than ane,200 combined hours of work.
Section 2
Three Noteworthy Categories of Mutual Airbnb Complaints
Out of 127,183 Airbnb guest complaints analyzed, hither is a breakdown of the near noteworthy examples of unpleasant (and sometimes dangerous) situations including scams, unsafe weather, and discrimination. Click the links below to navigate to that section of the folio where we also share poignant examples embedded directly from Twitter.
1. SCAMS (28,325 instances or 22.27% of all guest complaints)
- Multiple Listings of the Same Property (11,652 instances or 9.16% all guest complaints)
- Holding Not As Described (seven,286 instances or 5.73% of all guest complaints)
- Business relationship Hacked/ Fraudulent Charges (five,872 instances or 4.62% of all guest complaints)
- Fake Listings and/or Reviews (899 or 0.71% of all guest complaints)
- Other Scam or Fraud (2,616 or 2.06% of all guest complaints)
2. Dangerous Weather (7,719 instances or 6.07% of all invitee complaints)
- Infestations/ Unsanitary/ Unhealthy (4,305 or 3.38% of all invitee complaints)
- Serious Safe Concerns (1,274 or 1.00% of all guest complaints)
- Obnoxious Host and/or Environment (1,160 or 0.91% of all guest complaints)
- Unsafe or Cleaved Amenities (581 or 0.46% of all guest complaints)
- Hidden Cameras (251 or 0.20% of all guest complaints)
- Theft (149 or 0.12% of all invitee complaints)
3. Bigotry (four,851 or iii.81% of all guest complaints)
- Inability (2,891 or 2.27% of all guest complaints)
- Race (1,051 or 0.83% of all guest complaints)
- LGBTQ+ (153 or 0.12% of all guest complaints)
- Other Types of Bigotry (756 or 0.59% of all guest complaints)
SECTION 3
Five Types of Scams Plaguing Airbnb
Our analysis shows that scammers are utilizing dwelling house-sharing platforms to target unsuspecting victims. Although we can't quantify the exact amount, these tweets propose a serious problem. Since Airbnb is a recognizable brand, and the service appears comparable to that of hotels (see Binns and Kempf 2020: Safety and Security in Hotels and Dwelling house Sharing) users are most probable letting their guard downwardly and trusting the app. Guests expecting quality adaptation and service tin can be lured into a scam and announced to exist left with little recourse, equally is documented by tweets lament about the lack of customer support in these situations.
Our research has identified Airbnb scammers' five about common tactics to watch out for. Exist enlightened that there are myriad variations of these scams and scammers volition often effort to alter up their tactics equally consumers become more aware of them.
1. Multiple Listings of the Same Holding
This is by far the nigh common Airbnb scam reported in the set of analyzed Twitter complaints. The scam looks like this (with variations, of course):
- The host offers nice accommodation for a skillful price. Unbeknownst to the guest, the property was listed more than than in one case (on Airbnb and potentially other short-term rental platforms), once at a cheaper rate and one time at a much higher rate.
- If the host has a new guest make a booking at the college rate, they cancel the invitee who booked at the lower rate (usually last minute).
- Either the guest is out on the street on their own or the host offers a worse property without whatever discount.
- Airbnb may or may not arbitrate or offer back up on behalf of the guest, giving them few options but to take or be out the price of the original list, plus the cost of premium rates for last-minute accommodations elsewhere.
Cheque out some examples of this happening to guests:
Guest Examples of Multiple Listing Scams
Below discover several more examples of multiple listings scams in the press:
– The Points Guy : Travelers warn of last-minute holiday rental cancellations this summer
– WFTV nine : Families merits vacations were cancelled to charge new renters more than
– MakeUseOf : 3 Airbnb Scams You Need to Know About Before Booking Your Trip
– The Sun United kingdom : Airbnb hosts can abolish your reservation at the last minute as part of a 'scam' and there's goose egg you lot tin can do nearly it
– SFist : Acme ten Airbnb Scams Bamboozling Users Out of Money Across the World
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two. Property Not as Described
The second most unremarkably complained about scams are properties that are misleadingly marketed to make the accommodations appear better than they really are. This can be achieved through misdirection or staged photos containing civilities that no longer exist (or never existed in the first place). Naive guests go far at a home that is often drastically different from the photos and descriptions posted on the Airbnb platform e.chiliad. much dirtier than advertised or doesn't contain said luxury amenities, like a backyard hot tub or more uncomplicated essentials such as WiFi or running hot water.
Or, sometimes, the photos are complete lies. Guests arrive at the adaptation but to find out information technology is not at all what was advertised in the pictures, and they may have little recourse or opportunity for a full refund. Or if they are offered a full refund it could take weeks or months to receive the money-back.
Sometimes this scam will include the wrong accost. The host will "conveniently" claim that Airbnb mistakenly listed the accost and they tin't fix it. In this case, there is a good chance that the property owner has been booted off the platform before but has circumvented the brake by only listing a new address under a different proper noun. This scam personally happened to us in Paris in 2017.
Here are some examples of this scam in action:
Fifty-fifty more examples:
Guest Examples of Not every bit Described Scams
Below find several more examples of Airbnbs listings turning out not as described in the press:
– News 5 Cleveland : Texas mom says Cleveland Airbnb stay turned into a nightmare
– Newsweek : Woman Books Five-Star Airbnb, Turns Out to Exist 'Hoarder'due south Firm'
– SNN News : No A/C, cockroaches at pricey Siesta Key rental
– Toronto Sun: Time to shut the door on Airbnb
– KHOU : Woman says she was misled into booking basement room without windows, vents
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iii. Account Hacked & Fraudulent Credit Card Charges
Another unremarkably reported blazon of fraud that is extremely alarming is where scammers will hack into an Airbnb guests' business relationship (modify their password) and book multiple stays at potentially fake listings with the victim's credit bill of fare, debit menu, PayPal, or another associated payment method. The scammer will likely have ownership or connectedness to the property they have booked so that they are effectively doing a money transfer with the guests' finances. Information technology is plausible that the hacker is also using this tactic equally a money-laundering technique. The Airbnb guest is at present locked out of their business relationship may be missing thousands of dollars.
Many reports noted that customer service was not able to help them easily considering they "can't verify" the business relationship holder, keeping them stuck in this awful catch-22: can't go back up without their account, can't access their account without back up. And Airbnb has likely received acquirement via the scam regardless, in the form of booking fees. If Airbnb does manage to provide a resolution it can take weeks or longer for the guest to receive a total refund and it may not include all the booking fees.
It was unclear how these account hacks are occurring. However, the fact that this affected almost 5% of all users who complained via Twitter tells us that Airbnb'due south security measures and power to cake suspicious activeness could be improved. Often, guests reported that they believe that Airbnb itself is a scam, because of the lack of back up offered by the platform in recovering their account, or their funds.
Hither are some examples of this:
Even more examples:
Guest Examples of Account Hacked Scams
Below detect several more than examples of Airbnb account hacking scams in the press:
– USA Today : Airbnb users getting scammed with fake rentals, account closures
– Elliot Advancement : This is how I lost $1,181 to an Airbnb hacker (and got blocked, besides!)
– The Lord's day : Airbnb users complain of accounts being 'hacked' proverb they've been charged thousands and had bookings cancelled
– WKYC : Money Mon: Check your Airbnb account!
– Fox 13 Memphis : New scam targeting Airbnb accounts, charging people thousands in fake bookings
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4. Fake Listings & Reviews
Sometimes, guests will go far at what is clearly a completely different home than the ane pictured. Or, even worse, the listing never existed at all. Scammers will take pictures of homes off the net, list them as available rentals, and the unsuspecting guest shows up to cipher after losing out on hundreds or thousands of dollars. At the time of publishing this article, it is still possible to observe fake listings on Airbnb which suggests they take Non verified all their listings in 2021 even though they pledged they would by the terminate of 2020. This makes setting up simulated listings in sure jurisdictions fairly piece of cake to do.
Fake reviews are an increasingly prolific problem with the dwelling house-sharing platform. Imitation reviews completely undermine the integrity of the review process. If you don't know how genuine the reviews are, or if they were placed at that place by a less-than-genuine host, how can you know what yous and your family are walking into?
Here are some examples of fake listings and reviews:
Even more examples:
Guest Examples of Fake Listings Scams
Guest Examples of Fake Reviews Scams
Below detect several more examples of Airbnb imitation list scams in the printing:
– LifeHacker : How to Identify Scam Listings on Airbnb
– The Washington Mail : How to spot fake reviews on travel sites
– Traveller : Airbnb are removing some negative reviews. Here's why
– CNN : British couple spends $xi,800 on Airbnb rental in Ibiza that doesn't exist
– Forbes: Don't Go Duped: Spotting Fake Listings On Airbnb
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5. Other Airbnb Scams
In that location are enough of Airbnb scams that don't fall into a simple category. One example of this is the host demanding regional taxes upon arrival, or other various types of fees that were not outlined on the platform. They may insist that the guest cannot stay if they don't pay an actress $20, $50, or more than per night. Another example of this is upwards-charging amenities that were promised to be included in the list, like access to the pool or the washing machine but for a cash cost to exist paid direct to the host or listing manager.
Another common trick is where hosts point to Airbnb support that the guest damaged their property, when in fact they didn't, and so Airbnb could asking the guest pay additional fees.
I more well-known scam is when "hosts" contact guests during the pre-approval stage and send them a link to another website that looks exactly the same as Airbnb.com, merely isn't. Guests then log in once again and finalize the payment, just to realize after that they had sent money (likewise equally their cyberbanking info, and their Airbnb login data) to scammers who have no real list at all. These scammers usually practice get taken down from the platform, just information technology's possible for them to get dorsum on with some other fake scam listing.
Check these out hither:
Even more examples:
Guest Examples of Other Scams
Below find several more examples of other Airbnb scams in the printing:
– Irish Times : 'Alert bells started ringing': Friends lose €ii,600 in rental property scam
– Vice : Here Are the About Common Airbnb Scams Worldwide
– ABC Activeness News : 'I was scammed': Couple warns of 'sophisticated' rental scheme in St. Pete
– Q13 Fox : Woman falls victim to fake Airbnb site phishing fraud, says no ordinary rental scam
– CBD News : Airbnb customer who lost $3,700 warns others to avoid scammers
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Section four
Six Types of Dangerous or Unsanitary Weather condition at an Airbnb
Aggregate data can't fully paint the picture of what a guest goes through when they take a poor Airbnb experience. To demonstrate the frustrating, complicated, messy, and sometimes dangerous circumstances that countless guests accept experienced, we've compiled 500+ examples with photograph show of the thousands of "dangerous conditions" complaints shared past dissatisfied customers.
Please notation: the below examples are only the complaints that included photos. Guests tin can't easily or safely capture some of the more frequent complaints in images (aggressive hosts, certain serious prophylactic concerns, carbon monoxide, and cigarette smoke, for instance).
ane. Infestations, Unsanitary, and Unhealthy Accommodations
Of the "Unsafe Weather condition" complaints we analyzed, more than half pertained to the cleanliness and hygiene of the listing. Mutual problems include issues infestations, rodents, pests, mold, bodily fluids, rotting food, and other unsightly or unsafe living conditions. In the age of Covid-nineteen, cleanliness is of extra importance and lack of hygiene tin pose a real safety hazard.
Conditions range from inconvenient to downright precarious. Many Airbnb guests report dealing with sanitation problems long later on their visit, in the class of pests in their luggage (bedbugs, cockroaches) or residual wellness bug associated with things similar carbon dioxide poisoning, asthma, and mold. Other times, the issue was limited to dirty bedding, dishes in the sink, trash in the living area, and a general lack of cleanliness.
Below are two good examples of problems and rodent problems at an Airbnb.
Hundreds of more than photo examples shared by guests
Below are almost 300+ more than examples of complaints regarding unsafe and unhealthy conditions found at Airbnbs effectually the world.
66 Examples of Bug Infestation & Problems Bites
62 Examples of Mold & Mildew
25 Examples of Rats & Rodents
43 Examples of Dirty Bedding & Linens
eighteen Examples of Listings Not Cleaned Later on Last Guest
13 Examples of Feces Related Issues
iv Examples of Condom Wrappers
68 Examples of Other Filthy, Smelly, Unhealthy, Unsanitary
Examples shared by media outlets around the earth
Beneath find several more examples of infested, unsanitary or unhealthy conditions found at an Airbnb shared by the printing:
– The Boston Globe : How to navigate an Airbnb disaster, bugs and all
– CNet : Bedbugs are giving Airbnb users headaches… and itchy bites
– NL Times : Airbnb blamed for ascension in bedbug infestations
– The Boston World : How to navigate an Airbnb disaster, bugs and all
– Mirror : Airbnb guest books NYC room – but it's a cupboard with 'muddied' camping mattress
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two. Serious Safe Concerns
Serious safe concerns represent a dark possibility for Airbnb users. Guest complaints range from police interventions, assaults on guests, dangerous neighborhoods, drugs, drug deals, and weapons establish in the rental. While serious safety concerns remain a frequently Tweeted complaint, it is both difficult and unsafe to describe safe concerns in pictures, so we were only able to capture 8 images out of hundreds of concerning complaints around invitee safety and wellbeing.
Below are two examples of serious safety problems at Airbnbs.
And even more examples:
5 Examples of Guns, Bullet-related
three Examples of Harassment, Assault
Beneath detect several more examples of serious rubber concerns in Airbnbs shared by the press:
– Bloomberg : Male parent Says Airbnb Aid After Daughter's Death Was Damage Control
– The Hill : Consumer safe agency asks Airbnb, others to issue warnings on home elevators following child's decease
– NBC Boston : Airbnb Host Cancels Vacation Rental Later on Guest Asks About Camera Surveillance
– WRDW : Aiken man recorded minor female guest during stay, another lawsuit alleges
– Los Angeles Times : Deadly shootings highlight Airbnb's house party problem
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3. Obnoxious Host, Neighbors, and Environment
For Airbnb, a host tin really brand or interruption a stay. This category outlines the issues surrounding Airbnb hosts and the environment or neighborhood of a belongings. The bulk of complaints centered around inappropriate/aggressive hosts or unsafe neighborhoods, but compounding bug, including scams, discrimination, cancellations, and unpleasant living environments are frequently indicated problems within this section.
Hither are two telling examples of obnoxious houses, neighbors, and environments.
Check out these 68 more than examples.
3 Examples of Host Canceling Stay (Often Last Minute)
5 Examples of Ignored Covid Cancellation Requests
nine Examples of Objectionable Signs, Decor, Rules
10 Examples of Other Issues with Host
5 Examples of Website Issues
thirteen Examples of Other Harms, Potential Safety Problems
2 Examples of Other Misc. Complaints Against the Company
Below discover several more examples of obnoxious hosts, neighbors, and environments establish at an Airbnb shared past the printing:
– Wired : Threats, fear and anarchy: the messy fall of an Airbnb scam empire
– Fox : Local adult female out thousands of dollars after booking fake property on what she idea was Airbnb
– Vocalization : A bunko scam ran unchecked on Airbnb. Here's how it worked
– NZ Herald : Airbnb said no more than business firm parties. Why hasn't the letting app cleaned up its act?
– CBC : Airbnb quietly close down a elevation host among scathing reviews, just hundreds of guests were left to stay with him
– Traveller : Traveller Messages: Airbnb host refused refund, told united states of america to ignore lockdown rules
– CBC : Airbnb quietly shut down a top host amid scathing reviews, just hundreds of guests were left to stay with him
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4. Unsafe, Broken, or Missing Civilities
Many guests were promised amenities that turned out to be unsafe or not working as indicated on the Airbnb website. We were surprised to discover hundreds of examples of gas leaks, missing carbon monoxide and smoke detectors, and other electrical and fire hazards. This category also included things like missing keys and broken toilets.
Tragically, just terminal week, a Californian couple and their babe were found expressionless in an Airbnb likely because of a gas leak.
Here are four examples of unsafe or broken civilities.
Cheque out 92 more than examples.
17 Examples of Cleaved, Faulty Doors, Windows, Ceilings
5 Examples of Missing, Broken, Dangerous Furniture
12 Examples of Missing, Broken, Unsafe Appliances
5 Examples of No H2o, Dirty Water
12 Examples of No Estrus, No Hot Water
7 Examples of H2o Leaks
3 Examples of Fires & Fire Hazards
6 Examples of Electric Concerns
eight Examples of Other Missing, Broken, Non Working Ammenities
26 Examples of Other Unexpected, Described Listings
Beneath find several more examples of unsafe, broken or missing ammenities found at Airbnbs shared by the press:
– News 4 : Short-term rental companies reject refunds in Tahoe despite nearby fire, air quality
– WPCO Cincinnati : Airbnb rental turns out to be a windowless basement
– Popsugar : I Got to an Airbnb, and It Was a Nightmare — Here'south What Happened Next
– Gothamist : City Sues Over Alleged Airbnb Housing Band That Made Millions
– Honey: Adult female horrified after 'five-star' AirBnB is covered in rubbish and looks like a 'hoarder's paradise'
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5. Subconscious Cameras
Hidden cameras are a huge privacy violation and safety concern for many Airbnb guests. Though the hidden camera complaints merely account for a fraction of our analyzed complaints, information technology all the same represents a worrying trend for guests who want to experience private and condom in the listing they've paid for.
Airbnb's official stance on the issue of security cameras is that they have to exist disclosed in the listing description. However, in guild to accept a "subconscious camera", that rule is being cleaved as indicated by guest complaints on Twitter.
It also has to exist stated that as camera technology advances, guests may struggle to find the cameras being hidden in fume detectors, iPhone charging docks, USB adapters, and other clever hiding spots.
Beneath are ii good examples of cameras subconscious in Airbnbs.
Cheque out this recent TikTok video from @malwaretech where he shows you exactly how to find hidden cameras in an Airbnb and merely how easy it is for a voyeuristic host to muffle them.
@malwaretech Reply to @safarijackza How to find hidden cameras in AirBnBs ##prophylactic ##travel
♬ original sound – Marcus Hutchins
19 Examples of Hidden Cameras
Below observe several more examples of hidden camera stories in Airbnbs shared past the printing:
– The Atlantic : Airbnb Has a Hidden-Camera Trouble
– SFGATE : Nosotros rented a California vacation domicile and got spied on by a surveillance camera
– NBC Boston : Airbnb Host Cancels Holiday Rental Later Invitee Asks About Camera Surveillance
– WRDW : Aiken human recorded minor female guest during stay, another lawsuit alleges
– Sky News : Family discovers hidden camera livestreaming in Airbnb
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6. Stolen Property & Theft
Theft was the least common blazon of unsafe incidents in our dataset. For those who complained most theft, the biggest factor was improperly secured listings (sometimes where the thief had a key) or dangerous neighborhoods where thefts might more easily take place.
Here are ii examples of stolen property.
Cheque out several more examples.
5 Examples of Theft of Invitee Holding
Below find several more examples of thefts at Airbnbs shared by the printing:
– Washington Postal service : They booked an Airbnb for a Christmas getaway. Then their presents and holding were stolen
– KHOU Houston : Bachelorette weekend nightmare: Houston Airbnb apartment removed from site after thief targeted women
– News Channel 3 : Human being and woman defendant of robbing 6 guests at gunpoint at a Joshua Tree Airbnb
– Yeah Weekly : AIR B&E: Airbnb defendant of allowing scam artist to list Greensboro home
– WKRN : Airbnb burglaries persist in Nashville
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Section v
4 Common Forms of Discrimination
While complaints of discrimination only deemed for three.81% of our Twitter complaints, that is notwithstanding 4,851 people lament to Airbnb publicly via Twitter that they were treated poorly based on their race, orientation/gender expression, inability, religion, or for other discriminatory reasons. We've cleaved downwards the most common types of discriminatory experiences Airbnb guests have had, with existent-life examples from guests.
The sections are split upwardly into disability (2,891 complaints), race (1,051 complaints), LGBTQ+ (153 complaints), and other discrimination problems (756 complaints).
one. Inability-Based Discrimination
The ability for disabled individuals to take admission to rubber and accessible accommodations is an upshot that is plaguing the short-term rental economy. While hotels and established properties have accessibility standards to attach to, many private homes on Airbnb practice not.
For certain, disabled people should be protected nether the Americans with Disabilities Human action, many Airbnb guests observe that their bookings are canceled, their support animals are denied, or the listing that was "wheelchair attainable" was, in fact, very much not.
Here are some examples of disability bigotry:
Fifty-fifty more examples:
Guest Examples of Disability Discrimination
Below find more examples of Airbnb disability discrimination in the press:
– The Chat : Report shows how Airbnb hosts discriminate confronting guests with disabilities as sharing economic system remains in ADA greyness area
– The Verge : Airbnb hosts reject guests with disabilities more than often, researchers say
– Wired : Airbnb is massively failing travellers with disabilities
– Live + Well : How a Mother and Daughter Could Help Airbnb Improve Its Accessibility for Traveling Wheelchair Users
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2. Race-Based Discrimination
Thousands of guests get in to their rentals only to find that the host is rude, insulting or otherwise aggressive based on the their race. That is, if the guest fifty-fifty makes information technology to the bespeak of actually renting. Many guests detect that they may not even receive the booking based on diverse racial factors.
Check out some examples of this happening to guests:
Further examples of racism at Airbnbs:
Below discover several more examples of racism at Airbnb in the press:
– Fortune : How Racism on Airbnb Threatened My 20-Year Friendship
– iNews : In that location were plenty of Airbnbs available — until their hosts saw that I was black
– The Washington Post : 'Which monkey is gonna stay on the couch?': Airbnb host kicks out black guests in racist commutation
– Box : Airbnb has a bigotry problem. Inquire anyone who's tried to #Airbnbwhileblack.
– The Washington Post : 'One word says it all. Asian': Airbnb host reportedly leaves guest stranded because of her race
– Yahoo News : Airbnb algorithm linked to racial disparities in pricing
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iii. LGBTQIA-Based Discrimination
Members of the LGBTQIA+ customs accept also reported discrimination on the firm-letting platform. Some guests complain of poor reviews, mistreatment, or non being allowed to book rentals at all based on their LGBTQIA+ status.
Here are some examples of LGBTQIA+ bigotry in action:
Even more examples:
Invitee Examples of LGBTQIA+ discrimination
Beneath notice several more examples of LGBTQ+ discrimination:
– The Guardian : Airbnb faces outcry after transgender guest was denied stay by a host
– The Irish Times : Gay male couples 'discriminated confronting' by Dublin Airbnb hosts
– Thrillist : This LGBTQ-Friendly Alternative to Airbnb Helps Gay Travelers Experience Safe
– CNN: Traveling as a trans person: It's complicated
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4. Other Types of Bigotry
This category covers discrimination that doesn't fall into the category of race, LGBTQ+, or disabilities. These factors range from religious bigotry, prejudice based on nationality, age discrimination, size discrimination, pregnancy discrimination, and more.
Here are some examples of other types of discrimination in activity:
Even more examples:
Guest Examples of Other Forms of Discrimination
Below find several more examples of dissimilar kinds of discrimination in the press:
– Travel + Leisure: Fearing Islamophobic Airbnb hosts, entrepreneurs aim to build 'a Muslim-friendly solution'
– The Guardian : Airbnb adjourn on under-25s could be discriminatory, United kingdom of great britain and northern ireland lawyers warn
– Mirror : 'Fatphobic' Airbnb hosts tried to ban fatty people from staying in £199-a-nighttime cottage
– The Guardian : Airbnb suspends Victorian host who rejected couple for receiving Covid vaccine
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Section half dozen
Survey respondants report 24.two% had an Airbnb problem in the past year
When we conducted our original 2017 study nosotros had two carve up Airbnb customer service representatives tell us via the phone that "3% to 7% of Airbnb stays plow into a problem". However, for this research, we wanted to become the current situation on Airbnb and ran our ain online survey.
Below are our key findings.
What does Airbnb say?
According to an article written past Bloomberg:
"Airbnb says that fewer than 0.1% of stays upshot in a reported safety consequence, but with more than 200 million bookings a year, that'southward all the same a lot of trips with bad endings. Only the most serious bug are transferred to the internal condom team."
There are a few issues with this argument. Get-go of all, what constitutes a "reported safety upshot"? This opaque phrasing hardly clarifies what is considered a "serious safety concern". Are these only circumstances where guests undergo bodily harm or worse? And this doesn't even begin to capture all of the very expensive, frustrating, and upsetting issues that aren't "safety concerns", like the common complaints we place to a higher place.
But permit's too break downward Airbnb's numbers: 0.1% of 200 one thousand thousand stays a yr is 200,000 safety bug per year .
And this is only what Airbnb is willing to admit to.
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Department vii
Which cities get the most mentions on Twitter when an Airbnb guest has a problem?
We looked through our full dataset of 127,183 tweets for mentions of 100 popular tourist cities in the US and from around the globe and included the 50 with the nigh mentions below. Since this data is based just on Twitter mentions, it is not necessarily a true reflection of the most problematic cities, however, it is interesting to see a breakdown of which cities become the well-nigh complaints per one,000 Airbnbs (assuming each complaint is about a unique property) and how they compare to other popular destinations.
As well annotation, I shared this list on Reddit and made the frontpage with over 17,000 upvotes and 2,000+ comments from dissatisfied Airbnb customers sharing their experiences. The overwhelming Reddit consensus agreed with the ranking of many of the peak cities on the list and had people sharing their Airbnb horror stories.
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Department 8
Review manipulation problems
Guests are increasingly complaining of review manipulation on the platform. Not but are helpful details such equally star ratings (associated individual reviews) non nowadays on the platform, only many guests have also complained that their reviews accept been heavily altered or have disappeared altogether from listings they critically and honestly reviewed.
Scammers and Airbnb slumlords are going to great lengths to improve their listings with fake v-stars ratings. Wired Magazine outlined this do in an interesting article about how individuals and groups are ownership up cheap properties, taking misleading or outright fake photos of multiple listings, and saturating the listings with glowing, but very imitation, reviews from equally fake guests.
Details follow:
1. Critical reviews are being censored
Countless guests take noticed that their critical reviews are disappearing from the platform–or never making it onto the platform at all.
The Airbnb Review Policy has catchy language that allows Airbnb to essentially take down reviews for a number of reasons that often do good the hosts. Here'southward an instance of this in action:
"Circumstances entirely outside of another'southward control" is hard to quantify and could employ to many things that directly affect the guest experience, like noise, neighborhood, smell, safety. But, even for factors that would immediately impact the invitee experience, the host can petition to get these reviews taken downward using the opaque language of the policy. This ways a massive corporeality of negative reviews tin can be removed merely by virtue of the event being "exterior of some other'southward control".
The tweets nosotros analyzed complained that Airbnb refused to explicate what function of the comment violated their policy, leaving guests with no recourse nor fashion to communicate to future potential guests what's really going on in the rental units.
Hither is some other example of review censorship from a well-known travel adept – Jeremy from Travel Freak:
"I wrote a review almost my bad experience…which was promptly deleted from the Airbnb website simply days later on, and the entire trip had been removed from my history altogether. It was like my whole trip had just been deleted from their system. Like it never happened."
Hither is another case posted online by c 1000.
"We wrote a bad review of the place citing roaches, overall dated and dirty, no smoke warning etc. I put some positive things in the review as well. I was called a couple days afterwards writing the review proverb I had violated Airbnb policies… and my review was rejected… Airbnb made information technology impossible for me to put an honest review online."
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2. Lack of ability to anonymously provide feedback
Some of these issues around the review system may stem from the inability to leave anonymous reviews, which creates a sort of shame effectually leaving anything even hinting at critical. Every bit this Business Insider article suggests, having your proper name and face immortalized on the site alongside your negative feedback feels like a lot of pressure for guests who just desire to maintain a good reputation on the site that relies on reputation for remaining "in good continuing". That, combined with the fact that hosts can leave responses that can in turn set on the character or judgment of the initial reviewer means it can go ugly, fast. Additionally, guests worry that if hosts see critical reviews they've previously left, they will be denied future rentals because the host won't want a "picky" guest.
This phenomenon of mostly positive reviews is likely due to the "mutually assured destruction (or advantage)" of having both host and invitee reviewing one some other. The review system seems like it should be a good style for the community to monitor itself, and this does work in theory. Merely with the long documented history of review manipulation, hosts striking downwardly negative reviews, reviews not beingness listed chronologically and many critical reviews non making it to the website at all, it makes yous wonder what is even the point of a review process that tin't be trusted?
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iii. Reviews trend toward five-stars, fifty-fifty with glaring issues
Scrolling through the website or app, you'll notice that the majority of reviews are glowingly positive. Even on listings with subpar ratings, the reviews always tend to say really overnice, free things almost the space and the host. This makes you wonder, what's going on?
Sociolinguists take written inquiry papers titled, "If nearly all Airbnb reviews are positive, does that make them meaningless?" and psychologists have shared their thoughts on, "The anatomy of an Airbnb review. All adding to the conversation with this well-known issue of weird, saccharine reviewing tendencies on Airbnb.
Beneath we show an animated gif of the listing for a highly-rated Hawaiian Airbnb that has reviews that seem overwhelmingly positive. With a full score of iv.78, it'southward hard to argue that this is a very well-rated listing. Just add a small negative discussion and the truth speedily becomes credible.
Merely by searching the give-and-take "just", we see that this Airbnb is:
– "really dirty" (July 2021)
– "there's no Ac" (June 2021)
– "it's not a five-star hotel" (May 2021)
– "no private bath, no central air, no cupboard to hang up wearing apparel and strangers walk through your room to go to the washer and dryer" (April 2021)
– "no AC" (March 2021)
– "we institute cockroaches every night" (March 2021)
– "there is the neighbor's rooster" (January 2021)
– "the bathroom was quite messy" (January 2021)
– "information technology smelled a bit like smoke" (January 2021)
– "found the place to exist little dirty in maintenance." (December 2020)
Airbnb reviews with hidden meaning
And then we can rapidly see with a unproblematic search that this highly-rated destination list is actually a dirty, hot, cockroach-filled, smokey spot where strangers walk through the room on regular intervals. And it's rated four.78 with 353 reviews!
If you're planning to use Airbnb, I recommend you only stay at places rated 4.85 or above and spend time disecting all the reviews like a detective!
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4. Inability to filter reviews
Lastly, guests looking at a potential rental cannot filter reviews by ratings. Unlike many sites with user reviews like Amazon where you can, for case, see all the 1-star or 5-star ratings at once to get an thought of the range of guest experiences, Airbnb has no such filter selection by design. In fact, each individual review does non indicate the bodily rating at all, adding to the lack of transparency around how reviews operate on the site.
Department nine
Why is their customer service then notorious?
Airbnb is a massive company with a global reach. They avowal "v.6M+ listings in 220+ countries and regions". With a visitor of this size and with no costs of real estate, building maintenance, or typical hospitality staff, you would recall that Airbnb would invest in robust, quality customer service.
Co-ordinate to guests who share on Twitter, however, this is far from reality.
1. Overreliance on bots and AI
Typically when guests are experiencing an upshot with their listing, whether information technology's a simple inconvenience or a potentially dangerous crisis, dealing with a telephone tree of bots and AI is less than ideal. Only guests frequently complain of the seemingly increasingly automated nature of Airbnb's customer service.
Fifty-fifty with ane of the about successful means to become a response, their Twitter account, is coming under scrutiny as behaving like a bot, that leads to a DM bot, that leads… nowhere. A tool that checks the activity of a Twitter account called the Botometer created past Indiana University rates @AirbnbHelp a four.2/5 (higher scores mean more than bot-like activity).
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2. Responding fastest to public pressure (i.e. Twitter/Facebook)
Speaking of their Twitter, many guests have expressed frustration that the platform seems to respond quickest to public pressure and high-profile events, and not to their guests who really need information technology.
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iii. Asynchronyous and Confusing Customer Service
Co-ordinate to numerous guests on Twitter and other platforms, Airbnb assigns cases to specific agents (or "Support Ambassadors"). If that agent is overloaded or too busy to go back to you, then you're left waiting…
Instead of assuasive multiple agents to work on tickets as they are available, they seem to assign one Support Administrator and if that Back up Ambassador isn't working or isn't available, well, you'll but keep getting bounced back to them by all the other bots agents until they have the time to go to your ticket (out of, presumably, hundreds or thousands of tickets at whatever given time).
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4. Delays in refunds lasting weeks (or even months)
Fifty-fifty when the platform does promise to repay fees, partial refunds, or fifty-fifty full refunds, the money doesn't arrive for a long time. If at all.
Airbnb'due south lack of responsiveness leaves many, many travelers stranded in foreign countries with no place to stay, and no money to find concluding-minute, premium cost accommodations when their Airbnb doesn't work out. This is a scary, vulnerable situation for many who planned well in accelerate and did not think they would demand to anticipate paying for additional accommodations.
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Department 10
Class-action lawsuits
According to the Airbnb Terms of Service (that everyone agrees to but nobody reads), section 23.11 states (at the time of publishing this article):
"23.11 No Grade-Deportment or Representative Proceedings. You and Airbnb acknowledge and agree that, to the fullest extent permitted by law, we are each waiving the right to participate equally a plaintiff or course member in any purported form-action lawsuit, class-broad arbitration, private attorney full general action, or any other representative or consolidated proceeding."
I fairly regularly see comments shared past Airbnb users in the comment section of my blog and fifty-fifty on the official Airbnb community forum where people talk almost organizing class-action lawsuits. Airbnb's original Terms of Service did not have any "grade-activeness waiver" verbiage but by May 22, 2012, they had added it. The people wanting to participate in a class-activity adjust clearly have not read or take forgotten what they signed upward for when creating an account.
In the current version of the Airbnb Terms of Service, they effort to make the "class-action waiver" part of the agreement clear by putting a note about information technology at the very superlative of the agreement as this screenshot shows.
Basically, Airbnb is attempting to prevent y'all from participating in a grade-action lawsuit. Even for federally-protected reasons, like racial bigotry. Class-action waivers are condign more than common and are quite a controversial topic in the legal field. According to an article on The New York Times, "Class-action cases have been the merely effective mode to prove and remedy systemic discrimination considering you tin can't show a pattern of behavior with individually filed cases," said Joanne Doroshow, executive director of New York Law School'southward Center for Justice and Democracy, who specializes in civil justice issues.
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Department eleven
xi Key safety tips that will aid you avoid Airbnb horror stories
i. Never book a identify with goose egg reviews
Ideally, look for a minimum of 50 reviews in popular tourist areas or 25 in quieter areas. New listings are oft a blood-red flag because many times a host will remove a poorly-rated list and re-listing it instead of improving the actual space. This is how we concluded up getting scammed in Paris.
2. Only stay at places with a 4.85-star review average or college
Nigh people will only leave less than that if they have had a truly horrible feel. And in today'due south weirdly skewed Airbnb rating economic system, leaving a 5-star review is normal and anything much less than a iv.85 nearly guarantees something is sub-par with the accommodation. Many people volition even exit a 5-star at a bad listing, out of guilt, to avoid confrontation, or out of fearfulness of retaliation (feedback can exist argued with by hosts, which can reflect poorly on the guest). Nobody wants bad feedback on their invitee profile either.
3. Vet reviews very carefully
Additionally (and paradoxically), be mindful that Airbnb appears to censor reviews, and hosts are more oftentimes being cited equally manipulating ratings and inflating their overall rating with artificial reviews. For this reason, I recommend you read all the reviews to make up your own mind of how legitimate the reviews are, and what are the specific concerns other travelers have noted.
4. Use the "Search" characteristic to your reward
E'er use the review search feature to check reviews for keywords similar "not", "but", "bugs", "dissonance", "wifi", "dirt", "mold", "linens", "neighbors", "scent", "host", "rude", "cancel", "refund", "recommend", etc.
Using the search feature for your specific sticking points will assist you apace identify if you are going to have a bad stay. Those with allergies, for example, may want to search "dander", or light sleepers will want to search "racket/noisy". Guests will oft cloak negative experiences inside mostly positive reviews, so the search function helps you lot identify potential concerns.
5. Remember that the vast majority of reviews will seem positive even if the guest was unhappy
Sociolinguist Dr. Camilla Vasquez suggests "reading between the lines" when it comes to Airbnb reviews, equally reviews tend to trend more positively on Airbnb according to her research, and "bad" reviews are typically written every bit "lukewarm". So whatsoever hint of things non coming across equally absolutely glowing from a invitee probably has undertones of dissatisfaction that may not seem immediately credible.
6. Don't just look at your listings reviews, expect at your host's overall reviews
Many hosts will have several listings and just considering one list has good reviews, doesn't necessarily hateful they're a proficient host. Check to see if they accept other rundown, dirty, undesirable properties on their profile before trusting the reviews of one listing solitary. If one of their properties is in disrepair, odds are they all are.
7. Apply Superhosts whenever possible
These are supposed to be experienced hosts who abolish less often, answer chop-chop, and have a four.8 rating or college. Because of the various metrics involved with becoming a Superhost, they are typically the most reliable hosts on the platform.
8. Only stay with hosts who have provided verified government ID
Many countries but need e-mail and phone verification, which means that poorly-rated hosts tin can hands circumvent any sort of ban or de-listing by apace making a new business relationship. And while Airbnb does not seem to consistently verify listings (despite previous promises to do so), having a host with an ID on file gives some semblance of security.
nine. Avert hosts who have more than a couple of properties listed, aka professional Airbnb landlords
Beyond the ethical issues effectually how Airbnb is affecting the housing and rental markets, professional Airbnb "landlords" frequently come with their own prepare of issues. It'southward much more likely, for example, that your host has little to no idea of the state of their property, choosing to outsource the cleaning and operations to employees. In our experience, we had no idea who we were really talking to, who had keys to our identify, who the point-of-contact was, and other of import factors. Additionally, scams tin can be known to be done every bit big operations, as reported in this well-known Vice commodity. There are many reasons to strongly favor small-scale, independent hosts over hosts that seem to run a "commercial Airbnb concern".
10. Communicate with your host before your stay
Before you lot arrive at the property, ask the host if you have any questions nearly anything you're not sure of. Location, safety, wifi, guest restrictions, pet questions, accessibility, and other important details that might not be outlined on the profile.
Communicating almost bank check-in/check-out times and whatsoever other details that need to be ironed out beforehand will salvage y'all the stress and frustration of doing it last minute.
eleven. Document anything that goes wrong with photograph and video bear witness for help with getting a refund
Avert going through the messy "he said, she said" with a host by taking your own photos of the holding before your stay and after your stay. Brand certain to get all the major hotspots like the bathroom, the kitchen, and any heavy traffic areas.
If your host tries to merits unfair damages or give a review that isn't right, being able to provide photographic receipts may salve y'all a huge headache (and a lot of coin). Make sure your photos have timestamps or metadata enabled.
For more tips on staying safe while traveling, bank check out our nearly popular packing lists below:
Africa | Alaska | Amsterdam | Aruba | Asia | Australia | Infant Travel Gear | Bahamas | Bali | Barcelona | Belize | Cabo San Lucas | Camping | Cancun | China | Colorado | Costa rica | Cruise | Day Hike | Disney World | Dominican Democracy | Dubai | Europe | Flight | Florida | Glacier NP | Grand Canyon NP | Greece | Hawaii | Republic of iceland | Bharat | Republic of ireland | Italy | Jamaica | Nippon | Kauai | Primal West | Las Vegas | London | Maui | Mexico | Miami | Moab | Morocco | New York | New Zealand | Paris | Portugal | Puerto Rico | Puerto Vallarta | Punta Cana | Road Trip | Rome | RV Trip | Scotland | Spain | Thailand | Theme Park Trip | 2 Week Trip | Yellowstone NP | Yosemite NP | Zion NP
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Department 12
Conclusion
Ultimately, we were able to answer our question on, "which Airbnb guest problems are most likely to exist complained about via Twitter" and via our online survey. We hope it'south been as useful and enlightening for you lot as information technology was for u.s..
If you lot're curious to see what'southward going on right now with Airbnb complaints you lot tin practise so by simply visiting the @AirbnbHelp Twitter profile which literally has 100s of problems reported per day.
Lastly, if you're looking for more than specific examples of Airbnb guest (or host) issues, I would be happy to see if I can easily notice them for yous. Just utilize our contact form and clearly state what y'all're hoping to find.
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Source: https://www.asherfergusson.com/airbnb/
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