Social networks such as Facebook are required to provide users with their personal data. However, these dumps do not provide users insight in overarching themes in their online behavior. In this poster, we discuss the development of Mother, a spatial hypertext system for visual data exploration. First insights include that the less obvious connections are more interesting and relevant to the user than very close semantic or temporal connections.
Titel | Hypertext as a Tool for Exploring Personal Data on Social Media |
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Medien | Proceedings of the 31st ACM Conference on Hypertext and Social Media (HT '20) |
Verlag | ACM |
Heft | --- |
Band | --- |
ISBN | --- |
Verfasser/Herausgeber | Eelco Herder, Daniel Roßner, Prof. Dr. Claus Atzenbeck |
Seiten | 135–136 |
Veröffentlichungsdatum | 2020-07-01 |
Projekttitel | --- |
Zitation | Herder, Eelco; Roßner, Daniel; Atzenbeck, Claus (2020): Hypertext as a Tool for Exploring Personal Data on Social Media. Proceedings of the 31st ACM Conference on Hypertext and Social Media (HT '20), S. 135–136. DOI: 10.1145/3372923.3404831 |