SIIRJun 16, 2017

Twigraph: Discovering and Visualizing Influential Words between Twitter Profiles

arXiv:1706.05361v25 citations
Originality Incremental advance
AI Analysis

This work addresses the need for better visualization of social media connections for users and analysts, but it appears incremental as it builds on existing similarity and clustering techniques.

The authors tackled the problem of visually exploring connections between Twitter profiles by proposing Twigraph, a methodology that identifies influential words to measure similarity and group profiles, achieving results that show the identified words are highly representative of relationships.

The social media craze is on an ever increasing spree, and people are connected with each other like never before, but these vast connections are visually unexplored. We propose a methodology Twigraph to explore the connections between persons using their Twitter profiles. First, we propose a hybrid approach of recommending social media profiles, articles, and advertisements to a user.The profiles are recommended based on the similarity score between the user profile, and profile under evaluation. The similarity between a set of profiles is investigated by finding the top influential words thus causing a high similarity through an Influence Term Metric for each word. Then, we group profiles of various domains such as politics, sports, and entertainment based on the similarity score through a novel clustering algorithm. The connectivity between profiles is envisaged using word graphs that help in finding the words that connect a set of profiles and the profiles that are connected to a word. Finally, we analyze the top influential words over a set of profiles through clustering by finding the similarity of that profiles enabling to break down a Twitter profile with a lot of followers to fine level word connections using word graphs. The proposed method was implemented on datasets comprising 1.1 M Tweets obtained from Twitter. Experimental results show that the resultant influential words were highly representative of the relationship between two profiles or a set of profiles

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