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Govegan: Exploring Motives and Opinions From Tweets.
This report is suggesting the beneficial effect of clustering microbloggers tweets from 60 hashtags relating to the issue of Veganism. Going Vegan is a well-known effect on health. We aimed to analyze tweets coming from casual Twitter users and twitter accounts representing the veganism society and industry. We cluster the group of discourse that coming from 60 and more hashtags. These tags include tweets that have tagged with #plantbaseddiet, #veganfood, #vegetarian, etc. We collected n=50,634 tweets and analyzed n=25,639 processed tweets. The result shows that sampled tweets, which includes 1) concerns about animal welfare; 2) sustainability (environment) 3) ways to live a healthier lifestyle (Health), and 4) methods and op-tions for Vegan (recipe). Although with 60+ hashtags, this grouping practice allows decision-making processes more manageable. This work not only demonstrates the application of a clustering algorithm to collate microblogs with different hashtags into groups of similar topics but also shown that it is possible to develop a platform for automatically assembling information on the same subject from a range of different microblogs. The application can significantly assist others, including academic re-searchers, or businesses, to quickly and effectively find information and knowledge from these sources. This application is possible for society looking for a healthy life.