Personality Traits and the Relationship with (Non-) Disclosure Behavior on Facebook

Ferwerda, Bruce; Schedl, Markus; Tkalčič, Marko

doi:10.1145/2872518.2890085

Cited by 17 publications

(6 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the last couple of years, it has been demonstrated that personality information can be extracted from social networking sites (SNSs) like Facebook (e.g., [2,35,42,73,81]), Twitter (e.g., [41,75]), and Instagram (e.g., [29-31, 36, 65], or a combination of such [89]). Being able to extract personality traits from SNSs caters the possibility for (music) applications to adjust their user interface based on our results.…”

Section: Discussionmentioning

confidence: 99%

Personality and taxonomy preferences, and the influence of category choice on the user experience for music streaming services

Ferwerda

Yang

Schedl

et al. 2019

Multimed Tools Appl

Self Cite

View full text Add to dashboard Cite

Music streaming services increasingly incorporate different ways for users to browse for music. Next to the commonly used "genre" taxonomy, nowadays additional taxonomies, such as mood and activities, are often used. As additional taxonomies have shown to be able to distract the user in their search, we looked at how to predict taxonomy preferences in order to counteract this. Additionally, we looked at how the number of categories presented within a taxonomy influences the user experience. We conducted an online user study where participants interacted with an application called "Tune-A-Find". We measured taxonomy choice (i.e., mood, activity, or genre), individual differences (e.g., personality traits and music expertise factors), and different user experience factors (i.e., choice difficulty and satisfaction, perceived system usefulness and quality) when presenting either 6-or 24-categories within the picked taxonomy. Among 297 participants, we found that personality traits are related to music taxonomy preferences. Furthermore, our findings show that the number of categories within a taxonomy influences the user experience in different ways and is moderated by music expertise. Our findings can support personalized user interfaces in music streaming services. By knowing the user's personality and expertise, the user interface can adapt to the user's preferred way of music browsing and thereby mitigate the problems that music listeners are facing while finding their way through the abundance of music choices online nowadays.

show abstract

Section: Discussionmentioning

confidence: 99%

Personality and taxonomy preferences, and the influence of category choice on the user experience for music streaming services

Ferwerda

Yang

Schedl

et al. 2019

Multimed Tools Appl

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, changes in self-representation should be considered a continuous variable. Previous studies have demonstrated that profile pictures can be quantified using fine-grained analyses to detect different features of online self-representation, which provide a powerful measurement to predict personality traits [ 17 , 33 ]. Therefore, future studies investigating the relations between profile pictures using these in-depth analyses, personality, and life satisfaction would provide insights into the roles of online self-representation in the subjective well-being of internet users.…”

Section: Discussionmentioning

confidence: 99%

Profile Pictures in the Digital World: Self-Photographs Predict Better Life Satisfaction

Hung

Lee

Peng

2021

IJERPH

View full text Add to dashboard Cite

Profiles pictures as online identities represent an extension of the user's self in the digital world. Changes in self-representation are responsible for reduced well-being in individuals in the offline world. However, whether profile picture selection predicts the well-being of internet users is unknown. To address this question, we tested the relationship between the type of profile picture (e.g., self-photographs or other pictures) used on social media and the life satisfaction of internet users, accounting for gender and personality traits that have been thought to relate to the selection of profile pictures. The results showed that individuals using self-photographs as profiles reported a higher level of life satisfaction compared to individuals using other pictures as profiles. This effect was influenced by gender, openness, and extraversion. Hierarchical regression and moderation analyses revealed that openness and profile type interacted to predict life satisfaction in women, while openness and profile picture independently predicted life satisfaction in men. Furthermore, extraversion directly predicted life satisfaction in both men and women. These results indicate that the consistency between one's online and offline self-representation may characterize internet users' well-being, with potential implications for digital wellness.

show abstract

“…Specifically related to the music domain, an increasing amount of work has been done on identifying related behaviors to these traits (e.g., [8,14,31]) as well as work that has proposed to incorporate these traits into personalization and adaptation solutions (e.g., [3,5,7,23]). Furthermore, attention has been given to implicitly acquire personality traits for personalization purposes by the use of (external) information sources, such as Facebook (e.g., [1,10]), Twitter (e.g., [26]), Instagram (e.g., [9,[11][12][13]22]), or a combination of such [30].…”

Section: Related Workmentioning

confidence: 99%

Exploring Online Music Listening Behaviors of Musically Sophisticated Users

Ferwerda

Tkalčič

2019

Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization

Self Cite

View full text Add to dashboard Cite

Due to the rise of available online music, a lot of music consumption is moving from traditional offline media to online sources. Online music sources offer almost an unlimited music collection to its users. Hence, how music is consumed by users (e.g., experts) may differ from traditional offline sources. In this work we explored how musically sophisticated users (i.e. experts) consume online music in terms of diversity. To analyze this, we gathered data from two different sources: Last.fm and Spotify. As expertise is defined by the ubiquitousness of experiences, we calculated different diversity measurements to explore how ubiquitous (in terms of diversity) the listening behaviors of users are. We found that different musical sophistication levels correspond to applying diversity related to specific kind of musical characteristics (i.e., artist or genre). Our results can provide knowledge on how systems should be designed to provide better support to expert users. CCS CONCEPTS• Information systems → Recommender systems; • Human-centered computing → User models; User studies.

show abstract

Personality Traits and the Relationship with (Non-) Disclosure Behavior on Facebook

Cited by 17 publications

References 16 publications

Personality and taxonomy preferences, and the influence of category choice on the user experience for music streaming services

Personality and taxonomy preferences, and the influence of category choice on the user experience for music streaming services

Profile Pictures in the Digital World: Self-Photographs Predict Better Life Satisfaction

Exploring Online Music Listening Behaviors of Musically Sophisticated Users

Contact Info

Product

Resources

About