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Found 11 papers, 1 papers with code
CURAJ_IIITDWD@LT-EDI-ACL 2022: Hope Speech Detection in English YouTube Comments using Deep Learning Techniques
Hope Speech are positive terms that help to promote or criticise a point of view without hurting the user’s or community’s feelings.
Are you a hero or a villain? A semantic role labelling approach for detecting harmful memes.
Identifying good and evil through representations of victimhood, heroism, and villainy (i. e., role labeling of entities) has recently caught the research community’s interest.
IIITDWD@TamilNLP-ACL2022: Transformer-based approach to classify abusive content in Dravidian Code-mixed text
As part of ACL-2022, organizers of DravidianLangTech@ACL 2022 have released a shared task on abusive category identification in Tamil and Tamil-English code-mixed text to encourage further research on offensive content identification in low-resource Indic languages.
SOA_NLP@LT-EDI-ACL2022: An Ensemble Model for Hope Speech Detection from YouTube Comments
The language of internet users has a big impact on peer users all over the world.
IIIT_DWD@LT-EDI-EACL2021: Hope Speech Detection in YouTube multilingual comments
Such inspirational comments are hope speech comments.
Offensive language identification in Dravidian code mixed social media text
The data set used for this study are in Tanglish (Tamil and English), Manglish (Malayalam and English) code-mixed, and Malayalam script-mixed.
IIIT_DWD@EACL2021: Identifying Troll Meme in Tamil using a hybrid deep learning approach
The dataset used in the study is a part of the competition EACL 2021: Troll Meme classification in Tamil.
Enabling Quantum Natural Language Processing for Hindi Language
We present the process of building the parameterized quantum circuits required to undertake QNLP on Hindi sentences.
Hope Speech Detection on Social Media Platforms
Since personal computers became widely available in the consumer market, the amount of harmful content on the internet has significantly expanded.
IIITDWD-ShankarB@ Dravidian-CodeMixi-HASOC2021: mBERT based model for identification of offensive content in south Indian languages
Task 1 involves identifying offensive content in Malayalam data, whereas Task 2 includes Malayalam and Tamil Code Mixed Sentences.
Ranking Online Consumer Reviews
The product reviews are posted online in the hundreds and even in the thousands for some popular products.
