Was the 2019 Indian election won by digital media?

Neyazi, Taberez Ahmed; Schroeder, Ralph

doi:10.1080/10714421.2021.1933311

Cited by 11 publications

(6 citation statements)

References 41 publications

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“…Modi's Twitter campaign clearly demonstrates why his online presence is considered the most impressive among global political leaders (Pal, 2016). The Modi-led BJP having won the 2019 national election with a clear majority, one can see how his social media campaigns played a decisive role in this resounding victory (Neyazi & Schroeder, 2021).…”

Section: Discussionmentioning

confidence: 99%

Does Endorsement from Political Elites Affect Tweeting Behaviour? Studying the Effects of Indian Prime Minister Narendra Modi’s Tweets in 2019

Neyazi

Haque

2022

Preprint

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Does interactivity on Twitter by political elites yield dividends either in terms of a direct outcome (winning elections) or an indirect outcome (political mobilizations)? We answer this question using a unique dataset of Twitter users (N=27,640) who were among those thanked for their support by the Indian Prime Minister Narendra Modi in his tweets on 16thMarch, 2019 during his campaigning for the general election. We extracted tweets (tweets, retweets and replies) from these users from 10thJanuary (beginning of the campaign) to 19th May 2019 (the day the election ended), which yielded a total of 36.62 million tweets, and proceeded to classify these users based on their activeness on Twitter, for a comprehensive analysis of their Twitter activity over a period of 18 weeks to understand the impact of Modi’s intervention. A controlled intervention analysis using Autoregressive Integrated Moving Average (ARIMA) models was carried out with a control group comprising a similar set of Twitter users (N=27,610) supporting Modi's campaign, but were not mentioned by Modi. Our results suggest that, on average, the aggregate number of tweets shared by users had increased after mentions by Modi. However, our findings do not provide any evidence for the prominence of the activation behavior among less active Twitter users. We discuss the implications of our findings for the use of Twitter by political elites during electoral campaigns. Inferences about political activity on Twitter may also offer important insights into overall political activeness outside Twitter, as evidenced by the use of Twitter activity to capture social trends validated by other studies.

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Section: Discussionmentioning

confidence: 99%

Does Endorsement from Political Elites Affect Tweeting Behaviour? Studying the Effects of Indian Prime Minister Narendra Modi’s Tweets in 2019

Neyazi

Haque

2022

Preprint

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“…Also, in such cases, it is quite natural that the enthusiasm of local workers or leaders would be less due to a lack of personal attachment. Elections in India have become a display of money power, and a massive amount of money (directly/indirectly) is needed to contest elections (Neyazi and Schroeder, 2021).…”

Section: Discussionmentioning

confidence: 99%

Celebrity Brand Personality and Politics in West Bengal: An Explorative Study

Biswas

2022

Journal of Asian and African Studies

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Marketers have traditionally utilized celebrities to boost brand appeal by attracting attention and increasing memory rates, which is true in politics. However, research on the impact of celebrities on politics is new, and results are varied as to whether their endorsements and statements help in changing voters’ attitudes and behaviors. This study aimed to explore the effect of celebrity endorsement for a political party or celebrity candidate on people’s voting behavior. This is a mixed methods study. A community-based cross-sectional design was adopted for the study at Kolkata port and Maniktala constituencies (authors refer to Kolkata city) in the Kolkata district of West Bengal. Thematic analysis was used for qualitative data in this study using NVivo 12, whereas data entry and analysis were carried out with the help of Excel and Stata for quantitative data. About 16% of respondents reported being entirely influenced by the actor or actress’s election campaign. In contrast, 24% are not affected. Three-fifths of the respondents are somewhat influenced. It may be inferred that celebrity endorsement in political campaigns is one of the main elements determining the likelihood of a particular political party or candidate winning or losing an election. At the same time, it cannot always be since various individuals have varied perspectives about each party, and not everyone supports a party or candidate just because their favorite celebrity endorses it. More study is needed to understand this neglected arena of research. Thus, this article focuses on credibility as a key dimension.

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“…So, it is necessary to understand the people's sentiments behind online conversations such as Twitter, Facebook, Instagram, etc., which allows us to take into consideration a broader audience that includes both in-direct and direct participants [3][4][5]. Currently, Twitter is one of the effective platforms for sharing informative messages related to other social media platforms [6,7]. In recent decades, numerous machine learning models are used for people's sentiment analysis, but the majority of the existing models focused only on the textual feature vectors for constructing vector representation of the Twitter data [8,9].…”

Section: Introductionmentioning

confidence: 99%

Effective Twitter Sentiment Analysis Using Deep Belief Network with Enhanced Dragonfly Optimization Algorithm

2023

IJIES

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In this research article, an effective model is implemented for predicting the outcome of the Indian general election 2019 and farmer's protest by utilizing the sentiment analysis of Twitter data. In the initial segment, the raw Twitter data are acquired from the Indian Political tweets 2019 and farmers protest tweets databases. Further, the denoising operations such as removal of unnecessary space, tabs, new-line, hashtag symbols, non-English characters, punctuations, numbers and special characters are used to enhance the quality of the acquired data. Then, the keyword trend analysis and topic modeling utilizing latent dirichlet allocations (LDAs) are performed for better data representation. Next, the extraction of the feature is carried out utilizing skip-gram and term frequency-document level frequency (TF-IDF) techniques, and further, the feature optimization is accomplished using enhanced dragonfly optimization algorithm (EDOA) for selecting the optimal feature vectors. In the EDOA, a Brownian motion is added for improving the probabilistic behaviors. Lastly, the selected features are given to the deep belief network (DBN) model to classify the people's sentiments into negative, neutral, and positive classes. The experimental evaluations demonstrated that the EDOA-DBN model has obtained 99.22% and 98.83% of accuracy on both Indian political tweets 2019 and farmers protest tweets databases, which are maximum related to other existing models.

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Was the 2019 Indian election won by digital media?

Cited by 11 publications

References 41 publications

Does Endorsement from Political Elites Affect Tweeting Behaviour? Studying the Effects of Indian Prime Minister Narendra Modi’s Tweets in 2019

Does Endorsement from Political Elites Affect Tweeting Behaviour? Studying the Effects of Indian Prime Minister Narendra Modi’s Tweets in 2019

Celebrity Brand Personality and Politics in West Bengal: An Explorative Study

Effective Twitter Sentiment Analysis Using Deep Belief Network with Enhanced Dragonfly Optimization Algorithm

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