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            <title>Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (TRAC-2018)</title>
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    <abstract>This paper describes the work that our team bhanodaig did at Indian Institute of Technology (ISM) towards TRAC-1 Shared Task on Aggression Identification in Social Media for COLING 2018. In this paper we label aggression identification into three categories: Overtly Aggressive, Covertly Aggressive and Non-aggressive. We train a model to differentiate between these categories and then analyze the results in order to better understand how we can distinguish between them. We participated in two different tasks named as English (Facebook) task and English (Social Media) task. For English (Facebook) task System 05 was our best run (i.e. 0.3572) above the Random Baseline (i.e. 0.3535). For English (Social Media) task our system 02 got the value (i.e. 0.1960) below the Random Bseline (i.e. 0.3477). For all of our runs we used Long Short-Term Memory model. Overall, our performance is not satisfactory. However, as new entrant to the field, our scores are encouraging enough to work for better results in future.</abstract>
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%0 Conference Proceedings
%T TRAC-1 Shared Task on Aggression Identification: IIT(ISM)@COLING’18
%A Kumar, Ritesh
%A Bhanodai, Guggilla
%A Pamula, Rajendra
%A Chennuru, Maheshwar Reddy
%Y Kumar, Ritesh
%Y Ojha, Atul Kr.
%Y Zampieri, Marcos
%Y Malmasi, Shervin
%S Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (TRAC-2018)
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico, USA
%F kumar-etal-2018-trac
%X This paper describes the work that our team bhanodaig did at Indian Institute of Technology (ISM) towards TRAC-1 Shared Task on Aggression Identification in Social Media for COLING 2018. In this paper we label aggression identification into three categories: Overtly Aggressive, Covertly Aggressive and Non-aggressive. We train a model to differentiate between these categories and then analyze the results in order to better understand how we can distinguish between them. We participated in two different tasks named as English (Facebook) task and English (Social Media) task. For English (Facebook) task System 05 was our best run (i.e. 0.3572) above the Random Baseline (i.e. 0.3535). For English (Social Media) task our system 02 got the value (i.e. 0.1960) below the Random Bseline (i.e. 0.3477). For all of our runs we used Long Short-Term Memory model. Overall, our performance is not satisfactory. However, as new entrant to the field, our scores are encouraging enough to work for better results in future.
%U https://aclanthology.org/W18-4407
%P 58-65

Markdown (Informal)

[TRAC-1 Shared Task on Aggression Identification: IIT(ISM)@COLING’18](https://aclanthology.org/W18-4407) (Kumar et al., TRAC 2018)

• TRAC-1 Shared Task on Aggression Identification: IIT(ISM)@COLING’18 (Kumar et al., TRAC 2018)

ACL

• Ritesh Kumar, Guggilla Bhanodai, Rajendra Pamula, and Maheshwar Reddy Chennuru. 2018. TRAC-1 Shared Task on Aggression Identification: IIT(ISM)@COLING’18. In Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (TRAC-2018), pages 58–65, Santa Fe, New Mexico, USA. Association for Computational Linguistics.