100) and manually annotate whether the tweet is related to the particular event or not. We report precision values of 87.0%, 98.0%, 100% and 97% for Article 370, CAA/NRC, COVID-19 and Farmer’s Protests respectively. Given a set of accounts and their tweets for an occasion, we receive user embeddings based on aggregate tweet embeddings (Rashed et al. Overall, we get hold of a combined precision of 95.6%. While these precision values are noisy estimates of the true precision values, it offers a sanity test for the classification methodology.
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We discover that while on COVID-19 there’s a confluence of influencers on the aspect of the government, on three different contentious issues round citizenship, Kashmir’s statehood, and farmers’ protests, it’s mainly authorities-aligned fan accounts that amplify the incumbent’s positions. We suggest that this technique provides insight into the political schisms in present-day India – www.pipihosa.com – , but additionally provides a way to check influencers and polarization in other contexts. As social media raises considerations of polarizing politics, worldwide, questions arise on the position of public figures who wield the power to affect the political discourse.
Writer is a class for revealed authors of fiction and non-fiction, it doesn’t embrace columnists who’re employed by news platforms. In an effort to capture event particular tweets, we use a Word2Vec (Mikolov et al. 2013) bag of phrases primarily based approach to categorise the collected tweets (Vijayaraghavan, Vosoughi, and Roy 2016). We first outline a set of excessive precision key phrases which can be indicative of the occasion. After obtaining a vector illustration of all the phrases, we increase each of the key phrases from the seed set, by computing the cosine similarity of pairs of phrases for all phrases in the vocabulary. We then filter tweets that contain at the least one of many keywords, and consequently train a Word2Vec mannequin on the filtered tweets.
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Since such an exercise would robotically exclude people of certain faiths from scrutiny and intensify attention towards others, it stoked fears of misplaced citizenship amongst Indiaâs Muslims and led to widespread protests all across the country. The first wave period was marked by the federal government announcing a nationwide lockdown, which triggered an exodus of low-income migrant employees from Indian cities to hinterlands, usually on foot, since transport strains were closed. COVID-19: We studied the tweets surrounding the continued COVID-19 pandemic in India up until March 2021, earlier than the second wave of the disaster started.
We categorized each influencer account into only one category, whichever they are primarily known by, thus a major sportsperson with enterprise pursuits is nonetheless categorized beneath sports activities. The Enterprise category consists of accounts of business institutions, their founders, and key workers. The Entertainment segment refers to individuals engaged in movies, tv, music, and vogue. Academia refers to accounts that largely work with higher training institutes and conduct research. The ultimate set of influencers is divided right into a 12 classes. Fan Accounts have to do with profiles that distinctly avow to support public figures or organizations, and consists of unofficial accounts devoted to actors, politicians and political events. The Activist category consists of grassroots organizers, leaders or distinguished members of nonprofits, associates of religious or quasi-religious organizations who present themselves as activists, or any who self-determine with the label.
