Journal article
Characterizing Political Campaigning with Lexical Mutants on Indian Social Media
Proceedings of the International AAAI Conference on Web and Social Media, v 18, pp 1237-1248
28 May 2024
Abstract
Increasingly online platforms are becoming popular arenas of political amplification in India. With known instances of pre-organized coordinated operations, researchers are questioning the legitimacy of political expression and its consequences on the democratic processes in India. In this paper, we study an evolved form of political amplification by first identifying and then characterizing political campaigns with lexical mutations. By lexical mutation, we mean content that is reframed, paraphrased, or altered while preserving the same underlying message. Using multilingual embeddings and network analysis, we detect over 3.8K political campaigns with text mutations spanning multiple languages and social media platforms in India. By further assessing the political leanings of accounts repeatedly involved in such amplification campaigns, we contribute a broader understanding of how political amplification is used across various political parties in India. Moreover, our temporal analysis of the largest amplification campaigns suggests that political campaigning can evolve as temporally ordered arguments and counter-arguments between groups with competing political interests. Overall, our work contributes insights into how lexical mutations can be leveraged to bypass the platform manipulation policies and how such competing campaigning can provide an exaggerated sense of political divide on Indian social media.
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Details
- Title
- Characterizing Political Campaigning with Lexical Mutants on Indian Social Media
- Creators
- Shruti Phadke - The University of Texas at AustinTanushree Mitra - University of Washington
- Publication Details
- Proceedings of the International AAAI Conference on Web and Social Media, v 18, pp 1237-1248
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Other Identifier
- 991021985197304721