Self-Disclosure and Perceived Trustworthiness of Airbnb Host Profiles

Ma, Xiao; Hancock, Jeffery T.; Mingjie, Kenneth Lim; Нааман, Мор

doi:10.1145/2998181.2998269

Cited by 148 publications

(180 citation statements)

References 27 publications

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“…Similar to dating sites (and now dating apps), users on sharing platforms tend to disclose information that allows them to present themselves in a way that is both desirable (Peterson & Siek, 2009) and attractive for the type of user they consider to be a good match (Tussyadiah, 2016). Furthermore, as on dating sites, users will utilize the private information available to evaluate the trustworthiness of other users, regardless of whether they are participating in the sharing economy as consumers or as providers (Ert, Fleischer, & Magen, 2016;Ma, Hancock, Mingjie, & Naaman, 2017).…”

Section: Figure 1: Summary Of the Data Exchange For Consumers And Promentioning

confidence: 99%

“…Consumers will disclose information that makes them appear trustworthy and recommendable (Rosen, Lafontaine, & Hendrickson, 2011), hereby minimizing the uncertainty of providers (Lampinen & Cheshire, 2016). In this sense, impression management takes place in the kind of information disclosed (Yang, Quaan-Haase, Nevin, & Chen, 2017) but also in the amount, as studies have demonstrated that giving providers a complete profile can be crucial for minorities to receive the shared service (Ma et al, 2017).…”

Section: Privacy and Usersmentioning

confidence: 99%

“…Similar to a SNS, users will tend to share positive and intimate information to feel more connected to other users (Utz, 2015), and to generate positive impressions (Lee-Won, Shim, Joo, . Additionally to SNS, the potential revenues for consumers increases their need to achieve desirability with the information shared (Ma et al, 2017). Impression management also takes place with respect to the service or good offered, especially when the contact between providers and consumers is limited.…”

Section: Privacy and Usersmentioning

confidence: 99%

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Privacy in the Sharing Economy

et al. 2017

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Section: Figure 1: Summary Of the Data Exchange For Consumers And Promentioning

confidence: 99%

Section: Privacy and Usersmentioning

confidence: 99%

Section: Privacy and Usersmentioning

confidence: 99%

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Privacy in the Sharing Economy

et al. 2017

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“…The growing availability of online records of conversational traces provides an opportunity to mine linguistic patterns for markers of their presence. Past research in Web Mining and Natural Language Processing (NLP) studied aspects pertaining some of the dimensions we deal with in this work [34,78], with special attention to concepts at the extremes of the spectrum of sentiment such as conflict [70] or empathy [86,92] and support [109,114]. The operationalization of some of these concepts proved useful to improve the accuracy of prediction tasks [17,84,108,111].…”

mentioning

confidence: 99%

Ten Social Dimensions of Conversations and Relationships

Choi

Aiello

Varga³

et al. 2020

Proceedings of the Web Conference 2020

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Decades of social science research identified ten fundamental dimensions that provide the conceptual building blocks to describe the nature of human relationships. Yet, it is not clear to what extent these concepts are expressed in everyday language and what role they have in shaping observable dynamics of social interactions. After annotating conversational text through crowdsourcing, we trained NLP tools to detect the presence of these types of interaction from conversations, and applied them to 160M messages written by geo-referenced Reddit users, 290k emails from the Enron corpus and 300k lines of dialogue from movie scripts. We show that social dimensions can be predicted purely from conversations with an AUC up to 0.98, and that the combination of the predicted dimensions suggests both the types of relationships people entertain (conflict vs. support) and the types of real-world communities (wealthy vs. deprived) they shape.

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“…Such research approaches deal with drivers for renting out [70,73,121] and analyze the importance of monetary transactions in hospitality exchange networks [66]. Other studies were concerned with hosts' trustworthiness [48,83]. What has so far rarely been taken into account is hosts' potential to contribute to the discursive and performative reframing of residential neighborhoods into urban tourism areas, which is the focus of our work.Generally, user-generated content on information sharing platforms such as TripAdvisor has been identified as an important source of information for tourists [135].…”

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confidence: 99%

Constructing Urban Tourism Space Digitally

Stors

Baltes

2018

Proc. ACM Hum.-Comput. Interact.

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Over the past decade, Airbnb has emerged as the most popular platform for renting out single rooms or whole apartments. The impact of Airbnb listings on local neighborhoods has been controversially discussed in many cities around the world. The platform's widespread adoption led to changes in urban life, and in particular urban tourism. In this paper, we argue that urban tourism space can no longer be understood as a fixed, spatial entity. Instead, we follow a constructionist approach and argue that urban tourism space is (re-)produced digitally and collaboratively on online platforms such as Airbnb. We relate our work to a research direction in the CSCW community that is concerned with the role of digital technologies in the production and appropriation of urban space and use the concept of representations as a theoretical lens for our empirical study. In that study, we qualitatively analyzed how the two Berlin neighborhoods Kreuzkölln and City West are digitally constructed by Airbnb hosts in their listing descriptions. Moreover, we quantitatively investigated to what extend mentioned places differ between Airbnb hosts and visitBerlin, the city's destination management organization (DMO). In our qualitative analysis, we found that hosts primarily focus on facilities and places in close proximity to their apartment. In the traditional urban tourism hotspot City West, hosts referred to many places also mentioned by the DMO. In the neighborhood of Kreuzkölln, in contrast, hosts reframed everyday places such as parks or an immigrant food market as the must sees in the area. We discuss how Airbnb hosts contribute to the discursive production of urban neighborhoods and thus co-produce them as tourist destinations. With the emergence of online platforms such as Airbnb, power relations in the construction of tourism space might shift from DMOs towards local residents who are now producing tourism space collaboratively. close to major sights and tourism-related facilities, and venture into residential neighborhoods-a phenomenon called off the beaten track or new urban tourism [55,85,94,95,121]. Short-term rentals seem to foster this development [53,55,67]. They enable all kinds of temporary city-users [86], such as cultural tourists, exchange students, temporary migrants, or business travelers, to stay in private apartments. However, only a fraction of urban residents participates in the practice of renting out rooms or apartments. Some of them are annoyed by the large influx of visitors to their neighborhood and the consequences for the urban structure resulting from large-scale short term rentals [33,56,91]. The impact of the fast-growing number of Airbnb listings, particularly in residential neighborhoods, has been controversially discussed in many cities around the world. Central topics of this debate were, among others, Airbnb's contribution to the transformation of residential neighborhoods and resulting gentrification processes [56,60], coming along with rent increase [89,106], changes in the social structure of ...

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Self-Disclosure and Perceived Trustworthiness of Airbnb Host Profiles

Cited by 148 publications

References 27 publications

Privacy in the Sharing Economy

Privacy in the Sharing Economy

Ten Social Dimensions of Conversations and Relationships

Constructing Urban Tourism Space Digitally

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