Enhancing Sentiment Analysis on Twitter Using Community Detection

William Deitrick, Benjamin Valyou, Wes Jones, Joshua Timian, Wei Hu
2013 Communications and Network  
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
more » ... e 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 Sen-tiWordNet 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.
doi:10.4236/cn.2013.53022 fatcat:j6t5co6ogbesdcrvoggcllro7u