“Elections nowadays aren’t the same, social-media have changed them a lot!” — Oh yes, me.

Over the past decade, usage of political social-media (mainly Twitter) accounts has skyrocketed. Many political leaders (& sometimes their families) are using Twitter as a preeminent mode of communication with their citizenry. However, this has led to some interesting problems. Not only American elections but also the recent elections of the world’s largest democracy, India, was also accused to be **‘Biased’ **due to social media influence (check out this article by ‘The Washington Post’ to get what I mean here). The bias, mainly in the form of polarized ‘public sentiments’, was injected by distorting the fragile fabric of social-media.

Thinking of American politics & Twitter, chances are President Donald J. Trump comes to your mind. Ever since the year 2015, when Trump launched his political campaign, he became infamous for his so-called negative, derogatory & somewhat provoking tweets. Give him, 280 character limit, he’ll translate it to a package consisting of the whole spectrum of emotions, sentiments, facts, and opinions (check out this article by ‘The New York Times’ to know the bulk of tweets which he plays with). Even _Vox _(famous American news and opinion website), in one of its articles, confirms that Trump tweets a lot, & the quantum is really out there.

All of the above facts, combined with my advanced-analytics knowledge made me think — can I develop a Live App that could keep a track on the social-media behavior of candidates fighting for the United States Presidential election, 2020?

#automation #topic-modeling #machine-learning #pyspark #nlp