IIITG-ADBU at SemEval-2020 Task 9: SVM for Sentiment Analysis of English-Hindi Code-Mixed Text
In this paper, we present the results that the team IIITG-ADBU (codalab username {`}abaruah{'}) obtained in the SentiMix task (Task 9) of the International Workshop on Semantic Evaluation 2020 (SemEval 2020). This task required the detection of sentiment in code-mixed Hindi-English tweets. Broadly, we performed two sets of experiments for this task. The first experiment was performed using the multilingual BERT classifier and the second set of experiments was performed using SVM classifiers. The character-based SVM classifier obtained the best F1 score of 0.678 in the test set with a rank of 21 among 62 participants. The performance of the multilingual BERT classifier was quite comparable with the SVM classifier on the development set. However, on the test set it obtained an F1 score of 0.342.
Code (0)
등록된 구현이 없습니다.
Tasks
Sentiment AnalysisMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
IIITG-ADBU at SemEval-2020 Task 12: Comparison of BERT and BiLSTM in Detecting Offensive Language
Task 12 of SemEval 2020 consisted of 3 subtasks, namely offensive language identification (Subtask A), categorization of offense type (Subtask B), and offense target identification (Subtask C). This paper presents the re…
Language IdentificationWorld KnowledgeIIITG-ADBU at SemEval-2020 Task 8: A Multimodal Approach to Detect Offensive, Sarcastic and Humorous Memes
In this paper, we present a multimodal architecture to determine the emotion expressed in a meme. This architecture utilizes both textual and visual information present in a meme. To extract image features we experimente…
IIITG-ADBU@HASOC-Dravidian-CodeMix-FIRE2020: Offensive Content Detection in Code-Mixed Dravidian Text
This paper presents the results obtained by our SVM and XLM-RoBERTa based classifiers in the shared task Dravidian-CodeMix-HASOC 2020. The SVM classifier trained using TF-IDF features of character and word n-grams perfor…
SemEval-2023 Task 12: Sentiment Analysis for African Languages (AfriSenti-SemEval)
We present the first Africentric SemEval Shared task, Sentiment Analysis for African Languages (AfriSenti-SemEval) - The dataset is available at https://github.com/afrisenti-semeval/afrisent-semeval-2023. AfriSenti-SemEv…
ClassificationSentiment AnalysisSentiment Classificationzero-shot-classification+1DUTH at SemEval-2017 Task 4: A Voting Classification Approach for Twitter Sentiment Analysis
This report describes our participation to SemEval-2017 Task 4: Sentiment Analysis in Twitter, specifically in subtasks A, B, and C. The approach for text sentiment classification is based on a Majority Vote scheme and c…
BIG-bench Machine LearningGeneral ClassificationInformation RetrievalSentiment Analysis+2