Identification of Sentiments and Polarization in Collections of Short Texts
This project examines the use of social media in political communication in the context of lbig data in terms of large collections of short texts. It is an interdisciplinary project that considers how “echo chambers” impact the promised democratization – a point of interest studied by scholars in the fields of engineering, network science, communication, and physics.
This project will examine computational approaches to detect the sentiments and polarization within large collections of short texts regarding topics of social significance (such as the Black lives matter and Me Too movements). Explorations combine political science theories with computational techniques such as natural language processing and social network analysis.
This is an interdiscipliniary project where you will interact with political scientists regarding elicitation and context regarding political dialogue and movements.
Python and python based frameworks will be utilized in this project along with social media context fetched from Twitter.