Liang Gou
Michelle Zhou
ABSTRACT
This paper presents an interactive visualization tool, PersonalityViz, to help people understand their personality traits derived from social media. The system uses the Linguistic Inquiry and Word Count (LIWC) text analysis tool and LIWC/Big Five personality correlations to compute a person's Big Five personality from one's tweets. It provides an interactive visual interface that allows a user to explore her personality traits over time, and examine the visual evidence to understand how the personality traits are derived from the relevant tweets.
Supplemental Material
- Golbeck, J., Robles, C., Edmondson, M., and Turner, K. (2011). Predicting personality from twitter. In Proc. of the 3rd IEEE Intl. Conf. on Social Computing, 149--156.Google Scholar
Cross Ref
- Liu, S., Zhou, M. X., Pan, S., Song,Y., Qian, W., Cai,W., and Lian X. (2012). TIARA: Interactive, TopicBased Visual Text Summarization and Analysis. ACM TIST 3(2): 25. Google ScholarDigital Library
- McCrae, R. R. and John, O. P. (1992). An introduction to the five-factor model and its applications. Journal of Personality 60 (2): 175--215.Google ScholarCross Ref
- Pennebaker, J. W., Francis, M. and Booth, R. (2001). Linguistic inquiry and word count: LIWC 2001. Mahway: Lawrence Erlbaum Associates.Google Scholar
- Yarkoni, T. (2010). Personality in 100,000 Words: A large-scale analysis of personality and word use among bloggers. Journal of Research in Personality, 44, 363--373.Google Scholar
Index Terms
- PersonalityViz: a visualization tool to analyze people's personality with social media
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