Abstract
Purpose – The purpose of this paper is to propose a Web application system for visualizing Twitter users based on temporal changes in the impressions received from the tweets posted by the users on Twitter. Design/methodology/approach – The system collects a specified user’s tweets posted during a specified period using Twitter API, rates each tweet based on three distinct impressions using an impression mining system, and then generates pie and line charts to visualize results of the previous processing using Google Chart API. Findings – Because there are more news articles featuring somber topics than those featuring cheerful topics, the impression mining system, which uses impression lexicons created from a newspaper database, is considered to be more effective for analyzing negative tweets. Research limitations/implications – The system uses Twitter API to collect tweets from Twitter. This suggests that the system cannot collect tweets of the users who maintain private timelines. According to our ques...
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