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020 ▼a 9781085750462
035 ▼a (MiAaPQ)AAI22585209
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 371
1001 ▼a Hu, Tianran.
24510 ▼a Decoding Human Behaviors from Social Media.
260 ▼a [S.l.]: ▼b University of Rochester., ▼c 2019.
260 1 ▼a Ann Arbor: ▼b ProQuest Dissertations & Theses, ▼c 2019.
300 ▼a 285 p.
500 ▼a Source: Dissertations Abstracts International, Volume: 81-03, Section: A.
500 ▼a Advisor: Luo, Jiebo.
5021 ▼a Thesis (Ph.D.)--University of Rochester, 2019.
506 ▼a This item must not be sold to any third party vendors.
520 ▼a Given its large user base, deep user engagement level, and comprehensive coverage on different human activities, social media offers us a novel and effective lens for observing, analyzing, and gaining better understanding on human behaviors. Our work leverages the data collected from various social media platforms, and attempts to decode human behaviors at both individual and collective levels. From a mobility perspective, we study the relations between human mobility and other aspects of our lives, such as shopping patterns and circadian rhythms. Furthermore, we draw an analogy between human activities across online communities and movements in the physical world. The analogy leads us to a series of findings on the striking similarities between the physical and cyber spaces, and suggests promising new research directions. From a language perspective, we investigate how people from different social groups express themselves. The discovered divergent language patterns reveal the unique features of social groups, such as their interests, perception, personality traits, and so on. We then broaden our study on language to emoji, a type of commonly used non-verbal cue in Computer Mediated Communication, and reveal intentions and effects of using emojis. Our work validates the effectiveness of using social media as the data source for decoding human behaviors. More importantly, our work reveals insightful findings on human behaviours in various aspects, and sheds newer light on our own lives.
590 ▼a School code: 0188.
650 4 ▼a Computer science.
650 4 ▼a Web studies.
650 4 ▼a Behavioral psychology.
690 ▼a 0984
690 ▼a 0646
690 ▼a 0384
71020 ▼a University of Rochester. ▼b Hajim School of Engineering and Applied Sciences.
7730 ▼t Dissertations Abstracts International ▼g 81-03A.
773 ▼t Dissertation Abstract International
790 ▼a 0188
791 ▼a Ph.D.
792 ▼a 2019
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15492918 ▼n KERIS ▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다.
980 ▼a 202002 ▼f 2020
990 ▼a ***1008102
991 ▼a E-BOOK