Reading Political Sentiment and mood of the Electorate through Twitter Data

In this day and age of social media, Twitter plays an important role when it comes to election campaigning. Twitter has been seemingly popular among leaders of the western world, but the advent of accessible and affordable internet connectivity had led to its inroads in the India electoral ecosystem...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Khanna, Abhirup (author)
مؤلفون آخرون: Bansal, Ananya (author), Agarwal, Amit (author), Maheshwari, Piyush (author)
منشور في: 2020
الموضوعات:
الوصول للمادة أونلاين:https://bspace.buid.ac.ae/handle/1234/3093
https://doi.org/10.1109/ICSPIS51252.2020.9340147.
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author Khanna, Abhirup
author2 Bansal, Ananya
Agarwal, Amit
Maheshwari, Piyush
author2_role author
author
author
author_facet Khanna, Abhirup
Bansal, Ananya
Agarwal, Amit
Maheshwari, Piyush
author_role author
dc.creator.none.fl_str_mv Khanna, Abhirup
Bansal, Ananya
Agarwal, Amit
Maheshwari, Piyush
dc.date.none.fl_str_mv 2020
2025-05-22T10:23:56Z
2025-05-22T10:23:56Z
dc.identifier.none.fl_str_mv Khanna, A. et al. (2020) “Reading Political Sentiment and Mood of the Electorate Through Twitter Data,” in 2020 3rd International Conference on Signal Processing and Information Security (ICSPIS), pp. 1–4.
https://bspace.buid.ac.ae/handle/1234/3093
https://doi.org/10.1109/ICSPIS51252.2020.9340147.
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv IEEE
dc.relation.none.fl_str_mv 2020 3rd International Conference on Signal Processing and Information Security (ICSPIS)1-4
dc.subject.none.fl_str_mv Twitter; Elections; BJP; India; Social Media
dc.title.none.fl_str_mv Reading Political Sentiment and mood of the Electorate through Twitter Data
dc.type.none.fl_str_mv Article
description In this day and age of social media, Twitter plays an important role when it comes to election campaigning. Twitter has been seemingly popular among leaders of the western world, but the advent of accessible and affordable internet connectivity had led to its inroads in the India electoral ecosystem. Major political parties have their twitter accounts with millions of active followers. Government departments and respective ministers are now using Twitter as a means of publicizing public interest schemes among their followers. Twitter is being used as a tool for addressing current followers and appealing to potential future voters. In this paper, we present a popularity analysis between two national parties, i.e. BJP and INC. The work discusses the extent of positive popularity each party enjoys in various cities in India. Twitter data is harvested for analysis from seventeen different cities spread across four different zones in India. We examine the growth of BJP and its prominence in certain social groups. The paper talks about the rise of Prime Minister Narendra Modi and his emergence as a nationwide leader. Finally, we present positive takeaways from our analysis that may interest any political pundit of Indian democracy.
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identifier_str_mv Khanna, A. et al. (2020) “Reading Political Sentiment and Mood of the Electorate Through Twitter Data,” in 2020 3rd International Conference on Signal Processing and Information Security (ICSPIS), pp. 1–4.
language_invalid_str_mv en
network_acronym_str budr
network_name_str The British University in Dubai repository
oai_identifier_str oai:bspace.buid.ac.ae:1234/3093
publishDate 2020
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spelling Reading Political Sentiment and mood of the Electorate through Twitter DataKhanna, AbhirupBansal, AnanyaAgarwal, AmitMaheshwari, PiyushTwitter; Elections; BJP; India; Social MediaIn this day and age of social media, Twitter plays an important role when it comes to election campaigning. Twitter has been seemingly popular among leaders of the western world, but the advent of accessible and affordable internet connectivity had led to its inroads in the India electoral ecosystem. Major political parties have their twitter accounts with millions of active followers. Government departments and respective ministers are now using Twitter as a means of publicizing public interest schemes among their followers. Twitter is being used as a tool for addressing current followers and appealing to potential future voters. In this paper, we present a popularity analysis between two national parties, i.e. BJP and INC. The work discusses the extent of positive popularity each party enjoys in various cities in India. Twitter data is harvested for analysis from seventeen different cities spread across four different zones in India. We examine the growth of BJP and its prominence in certain social groups. The paper talks about the rise of Prime Minister Narendra Modi and his emergence as a nationwide leader. Finally, we present positive takeaways from our analysis that may interest any political pundit of Indian democracy.IEEE2025-05-22T10:23:56Z2025-05-22T10:23:56Z2020ArticleKhanna, A. et al. (2020) “Reading Political Sentiment and Mood of the Electorate Through Twitter Data,” in 2020 3rd International Conference on Signal Processing and Information Security (ICSPIS), pp. 1–4.https://bspace.buid.ac.ae/handle/1234/3093https://doi.org/10.1109/ICSPIS51252.2020.9340147.en2020 3rd International Conference on Signal Processing and Information Security (ICSPIS)1-4oai:bspace.buid.ac.ae:1234/30932025-05-22T10:26:35Z
spellingShingle Reading Political Sentiment and mood of the Electorate through Twitter Data
Khanna, Abhirup
Twitter; Elections; BJP; India; Social Media
title Reading Political Sentiment and mood of the Electorate through Twitter Data
title_full Reading Political Sentiment and mood of the Electorate through Twitter Data
title_fullStr Reading Political Sentiment and mood of the Electorate through Twitter Data
title_full_unstemmed Reading Political Sentiment and mood of the Electorate through Twitter Data
title_short Reading Political Sentiment and mood of the Electorate through Twitter Data
title_sort Reading Political Sentiment and mood of the Electorate through Twitter Data
topic Twitter; Elections; BJP; India; Social Media
url https://bspace.buid.ac.ae/handle/1234/3093
https://doi.org/10.1109/ICSPIS51252.2020.9340147.