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Enhancing Sentiment Analysis on Twitter Using Community Detection 被引量:3
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作者 William Deitrick Benjamin Valyou +2 位作者 Wes Jones joshua timian Wei Hu 《Communications and Network》 2013年第3期192-197,共6页
The increasing popularity of social media in recent years has created new opportunities to study the interactions of different groups of people. Never before have so many data about such a large number of individuals ... The increasing popularity of social media in recent years has created new opportunities to study the interactions of different groups of people. Never before have so many data about such a large number of individuals been readily available for analysis. Two popular topics in the study of social networks are community detection and sentiment analysis. Community detection seeks to find groups of associated individuals within networks, and sentiment analysis attempts to determine how individuals are feeling. While these are generally treated as separate issues, this study takes an integrative approach and uses community detection output to enable community-level sentiment analysis. Community detection is performed using the Walktrap algorithm on a network of Twitter users associated with Microsoft Corporation’s @technet account. This Twitter account is one of several used by Microsoft Corporation primarily for communicating with information technology professionals. Once community detection is finished, sentiment in the tweets produced by each of the communities detected in this network is analyzed based on word sentiment scores from the well-known SentiWordNet lexicon. The combination of sentiment analysis with community detection permits multilevel exploration of sentiment information within the @technet network, and demonstrates the power of combining these two techniques. 展开更多
关键词 COMMUNITY Detection TWITTER SOCIAL NETWORKS SENTIMENT Analysis SentiWordNet Walktrap
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