VIBES: visualizing changing emotional states in personal stories

Online journals (blogs) provide not only an outlet for emotional self-expression, but also a space for social interaction and commiseration through the exchange of personal stories. However, the massive extent of the blogosphere can overwhelm users, restricting their ability to make meaningful connections to fellow bloggers. In this article, we present a system, VIBES, that extracts the important topics from a blog, measures the emotions associated with those topics, and generates a suite of visualizations of this information. Unlike previous research, which has focused on extracting global trends in opinion across the blogosphere, VIBES focuses on depicting the emotional trajectories of the storylines that persist throughout the life experiences of the individual. In user tests, a majority of participants agreed that the visualizations revealed the author's current emotional state and emotional development over time. VIBES has potential applications both in connecting users via shared emotional profiles on social networks, as well as facilitating self-reflection through private user status displays. It also offers a fresh perspective for studying emotions and modeling how they change over time, which has a number of applications in affective computing, including the creation of emotionally responsive interfaces.

[1]  Gilad Mishne,et al.  Deriving wishlists from blogs show us your blog, and we'll tell you what books to buy , 2006, WWW '06.

[2]  Saul Greenberg,et al.  Transient life: collecting and sharing personal information , 2006, OZCHI '06.

[3]  Jon Oberlander,et al.  Whose Thumb Is It Anyway? Classifying Author Personality from Weblog Text , 2006, ACL.

[4]  Henry Lieberman,et al.  Visualizing the affective structure of a text document , 2003, CHI Extended Abstracts.

[5]  Kristian J. Hammond,et al.  Compelling computation: strategies for mining the interesting , 2007 .

[6]  Christopher H. Brooks,et al.  An Analysis of the Effectiveness of Tagging in Blogs , 2006, AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs.

[7]  Razvan C. Bunescu,et al.  Sentiment analyzer: extracting sentiments about a given topic using natural language processing techniques , 2003, Third IEEE International Conference on Data Mining.

[8]  J. Kamps,et al.  Words with attitude , 2002 .

[9]  Bing Liu,et al.  The utility of linguistic rules in opinion mining , 2007, SIGIR.

[10]  Oren Etzioni,et al.  Extracting Product Features and Opinions from Reviews , 2005, HLT.

[11]  Jeffrey Barlow,et al.  Internet and American Life Project , 2006 .

[12]  Gilad Mishne,et al.  MoodViews: Tools for Blog Mood Analysis , 2006, AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs.

[13]  Henry Lieberman,et al.  A model of textual affect sensing using real-world knowledge , 2003, IUI '03.

[14]  Hang Li,et al.  Topic Analysis Using a Finite Mixture Model , 2000, Inf. Process. Manag..

[15]  David M. Pennock,et al.  Mining the peanut gallery: opinion extraction and semantic classification of product reviews , 2003, WWW '03.

[16]  Matthew Willis,et al.  An emotionally intelligent user interface: modelling emotion for user engagement , 2007, OZCHI '07.

[17]  Tianshun Yao,et al.  A Knowledge-based Approach to Text Classification , 2002, SIGHAN@COLING.

[18]  Lawrence Birnbaum,et al.  Reasoning Through Search: A Novel Approach to Sentiment Classification , 2007 .

[19]  David Nadeau,et al.  Semi-supervised named entity recognition: learning to recognize 100 entity types with little supervision , 2007 .

[20]  Jan Schmidt,et al.  Blogging Practices: An Analytical Framework , 2007, J. Comput. Mediat. Commun..

[21]  Soo-Min Kim,et al.  Determining the Sentiment of Opinions , 2004, COLING.

[22]  Hsin-Hsi Chen,et al.  Major topic detection and its application to opinion summarization , 2005, SIGIR '05.

[23]  Xu Ling,et al.  Topic sentiment mixture: modeling facets and opinions in weblogs , 2007, WWW '07.

[24]  Joseph Kaye,et al.  Understanding how bloggers feel: recognizing affect in blog posts , 2006, CHI Extended Abstracts.