DHOT-Repository and Classification of Offensive Tweets in the Hindi Language

Jha, Vikas Kumar; Hrudya, P.; Vinu, P N; Vijayan, Vishnu; Prabaharan, P.

doi:10.1016/j.procs.2020.04.252

Cited by 43 publications

(18 citation statements)

References 9 publications

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“…From their timelines, similar users whose hateful content they are sharing were also tracked. -Offensive Posts: Twitter API 3 was used to query a list of most common swear words in Hindi which were curated by [32]. -Defamation Posts: Viral news articles regarding defamation of either an individual or an organization are studied to decide the reality of the situation and then posts regarding similar topics were searched on all popular social media platforms and correctly annotated.…”

Section: Datamentioning

confidence: 99%

Overview of CONSTRAINT 2021 Shared Tasks: Detecting English COVID-19 Fake News and Hindi Hostile Posts

Patwa

Bhardwaj

Guptha

et al. 2021

Communications in Computer and Information Science

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Fake news, hostility, defamation are some of the biggest problems faced in social media. We present the findings of the shared tasks (https://constraint-shared-task-2021.github.io/) conducted at the CONSTRAINT Workshop at AAAI 2021. The shared tasks are 'COVID19 Fake News Detection in English' and 'Hostile Post Detection in Hindi'. The tasks attracted 166 and 44 team submissions respectively. The most successful models were BERT or its variations.

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Section: Datamentioning

confidence: 99%

Overview of CONSTRAINT 2021 Shared Tasks: Detecting English COVID-19 Fake News and Hindi Hostile Posts

Patwa

Bhardwaj

Guptha

et al. 2021

Communications in Computer and Information Science

View full text Add to dashboard Cite

show abstract

“…A novel dataset of 50k annotated fake news in Bengali language is released in [9]. A fastText-based model has been used by [11] for the classification of offensive tweets in the Hindi language written in Devanagari script. The authors also release an annotated dataset for the detection of Hindi language abusive text detection.…”

Section: Related Workmentioning

confidence: 99%

Coarse and Fine-Grained Hostility Detection in Hindi Posts Using Fine Tuned Multilingual Embeddings

Elangovan

Maurya

et al. 2021

Combating Online Hostile Posts in Regional Languages During Emergency Situation

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Due to the wide adoption of social media platforms like Facebook, Twitter, etc., there is an emerging need of detecting online posts that can go against the community acceptance standards. The hostility detection task has been well explored for resource-rich languages like English, but is unexplored for resource-constrained languages like Hindi due to the unavailability of large suitable data. We view this hostility detection as a multi-label multi-class classification problem. We propose an effective neural network-based technique for hostility detection in Hindi posts. We leverage pre-trained multilingual Bidirectional Encoder Representations of Transformer (mBERT) to obtain the contextual representations of Hindi posts. We have performed extensive experiments including different pre-processing techniques, pre-trained models, neural architectures, hybrid strategies, etc. Our best performing neural classifier model includes One-vs-the-Rest approach where we obtained 92.60%, 81.14%, 69.59%, 75.29% and 73.01% F1 scores for hostile, fake, hate, offensive, and defamation labels respectively. The proposed model (https://github.com/Arko98/Hostility-Detection-in-Hindi-Constraint-2021) outperformed the existing baseline models and emerged as the state-of-the-art model for detecting hostility in the Hindi posts.

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“…Studies Online detection [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [9], [39], [40], [41], [42], [43], [8], [44], [45], [46], [47], [48], [49] Offline detection [50], [51], [52], [53], [54], [7], [55], [56] Safety [57], [13], [58], [59], [60], [61],…”

Section: Categorymentioning

confidence: 99%

A Systematic Review of Computer Science Solutions for Addressing Violence Against Women and Children

et al. 2021

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Violence against women and children are public health issues of pandemic proportions. It is estimated that one in every three women worldwide have experienced physical, emotional or sexual violence. Similarly, each year one of two children are victims of some form of violence, including domestic aggression and bullying. Due to the widespread use of the Internet and social media, women and children are also now vulnerable to other types of violence such as cyber-bullying and online sexual or emotional harassment. To help alleviate these social problem, the use of computer sciences and related technologies has been leveraged in recent years. The Internet of Things, artificial intelligence, ubiquitous and mobile computing, pattern recognition, cloud computing, and similar technologies have been used to formulate solutions to detect and prevent violent acts. In this paper, a systematic review of some of the efforts that can help address the problem of violence against women and children is presented. This paper describes the current state-of-the-art of these contributions and identifies trends, architectures, technologies, and current open challenges. The survey was developed using a literature review of academic documents published from 2010 to 2020. The contributions were categorized in four application domains: online detection, offline detection, safety and education. Additionally, these contributions were further categorized based on the computer science approaches and technologies used: artificial intelligence, Internet of Things and digital serious games.

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DHOT-Repository and Classification of Offensive Tweets in the Hindi Language

Cited by 43 publications

References 9 publications

Overview of CONSTRAINT 2021 Shared Tasks: Detecting English COVID-19 Fake News and Hindi Hostile Posts

Overview of CONSTRAINT 2021 Shared Tasks: Detecting English COVID-19 Fake News and Hindi Hostile Posts

Coarse and Fine-Grained Hostility Detection in Hindi Posts Using Fine Tuned Multilingual Embeddings

A Systematic Review of Computer Science Solutions for Addressing Violence Against Women and Children

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