Visualizing Temporal Changes in Impressions from Tweets

Abstract

Twitter is effective for connecting with celebrities, on-screen talent, and strangers, as well as with friends and acquaintances, and is a social networking service utilized by several generations. On Twitter, many users will offer constructive suggestions, while a small number of users will sometimes enact mental abuse. Some users may post lively tweets, while other users may express anger in their tweets. By carefully reading a larger number of an individual user's tweets, it is possible to judge the impressions from tweets received from an individual user's typical posts. Therefore, this paper proposes a web application system for visualizing Twitter users based on temporal changes in the impressions from the tweets posted by users on Twitter. When system users input the account name of a Twitter user and a period for analysis, the proposed system collects the user's tweets posted during the period, quantifies the impressions from each tweet, and generates pic and line charts illustrating the impression values of the tweets and their temporal changes.