Findings of the Shared Task on Multi-task Learning in Dravidian Languages

Chakravarthi, Bharathi Raja; Priyadharshini, Ruba; Cn, Subalalitha; Sangeetha, S; Subramanian, Malliga; Shanmugavadivel, Kogilavani; Krishnamurthy, Parameswari; Hande, Adeep; Hegde, Siddhanth U; Nayak, Roshan; Valli, Swetha

doi:10.18653/v1/2022.dravidianlangtech-1.43

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…Other political parties also showed enthusiastic support as, according to Ashok, they viewed it as an opportunity to strengthen "Tamil identity". In his speech, Stalin mentioned another symbolic cue that has emotional ties with Indians -Keeladi, an important archaeological site in the state -where several pieces that were used to play a version of Chess which archeologists estimate to be from the 6th century, had been excavated (Chakravarthi et al 2022). It is clear from the lack of a vocal opposition by the political parties in the state that the price of 10 million USD was deemed a fair price to pay for the product which is a success in cultural diplomacy in the form of Chess Olympiad in Chennai.…”

Section: Product Price and Placementioning

confidence: 99%

Harmonizing Political and Marketing Aesthetics: Insights from The Chess Olympiad 2022

WS,

Christie

2024

Intl. J. Rel.

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This article explores how the Government of Tamil Nadu, India, utilised strategic mass communication methods that emerged from a fusion of political and marketing strategies to create an aesthetic approach that elevated Chess Olympiad 2022, an event typically less in the public eye, into a spectacle that captured widespread attention by focusing on the event’s impact on their cultural identity and the subsequent construction of a narrative of global cultural leadership. The marketing strategy of the Government of Tamil Nadu, India may be considered an aesthetic application of the theory of symbolic interactionism, as it employed literary, musical arts and visual arts across Chennai, that ensured active engagement of individuals in the city with the government's aesthetic representations. These visual representations acted as symbolic cues, inviting interaction and sparking the curiosity of the the whole host city, the Government of Tamil Nadu, India succeeded in turning Chess into a spectator sport, and by doing so, forged a key place in the national identity for Chess by building a narrative of collective linguistic and cultural identity. Since all citizens do not have an expert level knowledge on government policies, the media narrative that is built around any government policy determines its perceived success. The media narrative of Chess Olympiad 2022 was the narrative of India emerging as a global leader in cultural diplomacy - a soft power approach that is shaped by aesthetics. In dissecting the intricate interplay between mass communication, aesthetics, and societal identity formation, this study elucidates the transformative role of these strategies during the Chess Olympiad 2022, highlighting their profound implications within the socio-cultural landscape.

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Section: Product Price and Placementioning

confidence: 99%

Harmonizing Political and Marketing Aesthetics: Insights from The Chess Olympiad 2022

WS,

Christie

2024

Intl. J. Rel.

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“…The authors developed a comment corpus containing 35K manually labeled data for modelling the opinion polarity of the comments based on tree kernel models. Chakravarthi et al (2020a), Chakravarthi et al (2020b), Sampath et al (2022, Chakravarthi et al (2022b), andB et al (2022b) collected comments from YouTube and created a manually annotated corpus for the sentiment analysis, emotional analysis, offensive language identification, and multimodal sentiment analysis of the under-resourced Tamil and Malayalam languages. Methods to mitigate gender bias in natural language processing (NLP) have been extensively studied for the English language (Sun et al 2019).…”

Section: Related Workmentioning

confidence: 99%

Hope speech detection in YouTube comments

Chakravarthi

2022

Soc. Netw. Anal. Min.

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Recent work on language technology has tried to recognize abusive language such as those containing hate speech and cyberbullying and enhance offensive language identification to moderate social media platforms. Most of these systems depend on machine learning models using a tagged dataset. Such models have been successful in detecting and eradicating negativity. However, an additional study has lately been conducted on the enhancement of free expression through social media. Instead of eliminating ostensibly unpleasant words, we created a multilingual dataset to recognize and encourage positivity in the comments, and we propose a novel custom deep network architecture, which uses a concatenation of embedding from T5-Sentence. We have experimented with multiple machine learning models, including SVM, logistic regression, K-nearest neighbour, decision tree, logistic neighbours, and we propose new CNN based model. Our proposed model outperformed all others with a macro F1-score of 0.75 for English, 0.62 for Tamil, and 0.67 for Malayalam.

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