Developing insights from the collective voice of target users in Twitter

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Abstract
This study develops a pragmatic scheme that facilitates insight development from the collective voice of target users in Twitter, which has not been considered in the existing literature. While relying on a wide range of existing approaches to Twitter user profiling, this study provides a novel and generic procedure that enables researchers to identify the right users in Twitter and discover topical and social insights from their tweets. To identify a target audience of Twitter users that meets certain criteria, we first explore user profiling, potentially followed by text-based, customized user profiling leveraging hashtags as features for machine learning. We then present how to mine popular topics and influential actors from Twitter data. Two case studies on 16 thousand young women interested in fashion and 68 thousand people sharing the same interest in the Me Too movement indicate that our approach facilitates discovery of social trends among people in a particular domain.

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