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Tsinghua Science and Technology 2013, 18(2): 182-195 https://doi.org/10.1109/TST.2013.6509101
Open Access | Issue | Published: 30 April 2013

Portraying User Life Status from Microblogging Posts

Show Author's Information Jiayu Tang( ),  Zhiyuan Liu,  Maosong Sun,  Jiahua Liu
State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
Keywords:
sentiment analysis, topic model, text visualization, microblogging, keyword extraction
Cite this article:
Tang J, Liu Z, Sun M, et al. Portraying User Life Status from Microblogging Posts. Tsinghua Science and Technology, 2013, 18(2): 182-195. https://doi.org/10.1109/TST.2013.6509101
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Abstract Full text About this article

Microblogging services provide a novel and popular communication scheme for Web users to share information and express opinions by publishing short posts, which usually reflect the users’ daily life. We can thus model the users’ daily status and interests according to their posts. Because of the high complexity and the large amount of the content of the microblog users’ posts, it is necessary to provide a quick summary of the users’ life status, both for personal users and commercial services. It is non-trivial to summarize the life status of microblog users, particularly when the summary is conducted over a long period. In this paper, we present a compact interactive visualization prototype, LifeCircle, as an efficient summary for exploring the long-term life status of microblog users. The radial visualization provides multiple views for a given microblog user, including annual topics, monthly keywords, monthly sentiments, and temporal trends of posts. We tightly integrate interactive visualization with novel and state-of-the-art microblogging analytics to maximize their advantages. We implement LifeCircle on Sina Weibo, the most popular microblogging service in China, and illustrate the effectiveness of our prototype with various case studies. Results show that our prototype makes users nostalgic and makes them reminiscent about past events, which helps them to better understand themselves and others.


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About this article

Portraying User Life Status from Microblogging Posts

Show Author's information Jiayu Tang( ), Zhiyuan Liu, Maosong Sun, Jiahua Liu
State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China

Abstract

Microblogging services provide a novel and popular communication scheme for Web users to share information and express opinions by publishing short posts, which usually reflect the users’ daily life. We can thus model the users’ daily status and interests according to their posts. Because of the high complexity and the large amount of the content of the microblog users’ posts, it is necessary to provide a quick summary of the users’ life status, both for personal users and commercial services. It is non-trivial to summarize the life status of microblog users, particularly when the summary is conducted over a long period. In this paper, we present a compact interactive visualization prototype, LifeCircle, as an efficient summary for exploring the long-term life status of microblog users. The radial visualization provides multiple views for a given microblog user, including annual topics, monthly keywords, monthly sentiments, and temporal trends of posts. We tightly integrate interactive visualization with novel and state-of-the-art microblogging analytics to maximize their advantages. We implement LifeCircle on Sina Weibo, the most popular microblogging service in China, and illustrate the effectiveness of our prototype with various case studies. Results show that our prototype makes users nostalgic and makes them reminiscent about past events, which helps them to better understand themselves and others.

Keywords: sentiment analysis, topic model, text visualization, microblogging, keyword extraction

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Publication history

Received: 07 December 2012
Accepted: 19 February 2013
Published: 30 April 2013
Issue date: April 2013

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© The author(s) 2013

Acknowledgements

This research is supported by the National Natural Science Foundation of China (Nos. 61170196 and 61202140), and by the Singapore National Research Foundation under its International Research Centre @ Singapore Funding Initiative and administered by the IDM Programme Office.

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