KanCMD: Kannada CodeMixed Dataset for Sentiment Analysis and Offensive Language Detection
@inproceedings{Hande2020KanCMDKC, title={KanCMD: Kannada CodeMixed Dataset for Sentiment Analysis and Offensive Language Detection}, author={Adeep Hande and Ruba Priyadharshini and Bharathi Raja Chakravarthi}, booktitle={PEOPLES}, year={2020} }
We introduce Kannada CodeMixed Dataset (KanCMD), a multi-task learning dataset for sentiment analysis and offensive language identification. The KanCMD dataset highlights two realworld issues from the social media text. First, it contains actual comments in code mixed text posted by users on YouTube social media, rather than in monolingual text from the textbook. Second, it has been annotated for two tasks, namely sentiment analysis and offensive language detection for under-resourced Kannada…
51 Citations
Benchmarking Multi-Task Learning for Sentiment Analysis and Offensive Language Identification in Under-Resourced Dravidian Languages
- Computer ScienceArXiv
- 2021
Analysis of fine-tuned models indicates the preference of multi-task learning over single- task learning resulting in a higher weighted F1-score on all three languages, including Kannada, Malayalam and Tamil.
Offensive language identification in Dravidian code mixed social media text
- Computer ScienceDRAVIDIANLANGTECH
- 2021
The experimental results showed that 1 to 6-gram character TF-IDF features are better for the said task and the best performing models were naive bayes, logistic regression, and vanilla neural network for the dataset Tamil code-mix, Malayalam code-mixed, and Malayali script-m mixed.
Towards Offensive Language Identification for Tamil Code-Mixed YouTube Comments and Posts
- Computer ScienceSN Comput. Sci.
- 2022
A novel and flexible approach of selective translation and transliteration techniques are proposed to reap better results from fine-tuning and ensembling multilingual transformer networks like BERT, DistilBERT, and XLM-RoBERTa and are promising for effective offensive speech identification in low-resourced languages.
IIITT@Dravidian-CodeMix-FIRE2021: Transliterate or translate? Sentiment analysis of code-mixed text in Dravidian languages
- Computer ScienceArXiv
- 2021
The work for the shared task conducted by Dravidian-CodeMix at FIRE 2021 is described by employing pre-trained models like ULMFiT and multilingual BERT fine-tuned on the code-mixed dataset, transliteration (TRAI), English translations (TRAA) of the TRAI data and the combination of all the three.
Findings of the Shared Task on Offensive Language Identification in Tamil, Malayalam, and Kannada
- Computer ScienceDRAVIDIANLANGTECH
- 2021
A shared task on offensive language detection in Dravidian languages is created and an overview of the methods and the results of the competing systems are presented.
Sentiment Classification of Code-Mixed Tweets using Bi-Directional RNN and Language Tags
- Computer ScienceDRAVIDIANLANGTECH
- 2021
This work takes up a similar challenge of developing a sentiment analysis model that can work with English-Tamil code-mixed data by using bi-directional LSTMs along with language tagging using a Neural Network based model.
Offensive Language Identification in Low-resourced Code-mixed Dravidian languages using Pseudo-labeling
- Computer ScienceArXiv
- 2021
This work intends to classify code-mixed social media comments/posts in the Dravidian languages of Tamil, Kannada, andMalayalam to improve offensive language identification by generating pseudo-labels on the dataset.
HUB@DravidianLangTech-EACL2021: Identify and Classify Offensive Text in Multilingual Code Mixing in Social Media
- Computer ScienceDRAVIDIANLANGTECH
- 2021
This is the first task to detect offensive comments posted in social media comments in the Dravidian language and uses the multilingual BERT model to complete this task.
DOSA: Dravidian Code-Mixed Offensive Span Identification Dataset
- Computer ScienceDRAVIDIANLANGTECH
- 2021
The Dravidian Offensive Span Identification Dataset (DOSA) is presented, which provides span annotations for Tamil-English and Kannada-English code-mixed comments posted by users on YouTube social media, leading to an essential step towards semi-automated content moderation in Dravid languages.
CUSATNLP@DravidianLangTech-EACL2021:Language Agnostic Classification of Offensive Content in Tweets
- Linguistics, Computer ScienceDRAVIDIANLANGTECH
- 2021
This shared task is to identify offensive content from code mixed Dravidian Languages Kannada, Malayalam, and Tamil using language agnostic BERT (Bidirectional Encoder Representation from Transformers) for sentence embedding and a Softmax classifier.
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