GoVegan: Exploring motives and opinions from tweets - Teh, Phoey Lee *; Yap, W. L. (Springer, Cham, 2021)
This report is suggesting the beneficial effect of clustering micro bloggers tweets from 60 hash tags 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, #vegan food, #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 options for Vegan (recipe). Although with 60+hash tags, this grouping practice allows decision making processes more manageable. This work not only demonstrates the application of a clustering algorithm to collate micro blogs with different hash tags 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 micro blogs. The application can significantly assist others, including academic researchers, or businesses, to quickly and effectively find information and knowledge from these sources. This application is possible for society looking for a healthy life.