no code implementations • SemEval (NAACL) 2022 • Gagan Sharma, Gajanan Sunil Gitte, Shlok Goyal, Raksha Sharma
This paper presents our submission to task 5 ( Multimedia Automatic Misogyny Identification) of the SemEval 2022 competition.
no code implementations • GWC 2016 • Raksha Sharma, Pushpak Bhattacharyya
For fine-grained sentiment analysis, we need to go beyond zero-one polarity and find a way to compare adjectives (synonyms) that share the same sense.
no code implementations • WASSA (ACL) 2022 • Himil Vasava, Pramegh Uikey, Gaurav Wasnik, Raksha Sharma
This paper describes the contribution of team PHG to the WASSA 2022 shared task on Empathy Prediction and Emotion Classification.
1 code implementation • NAACL (SocialNLP) 2022 • Divyam Goel, Raksha Sharma
The last few years have witnessed an exponential rise in the propagation of offensive text on social media.
no code implementations • SEMEVAL 2021 • Vansh Gupta, Raksha Sharma
This paper describes and examines different systems to address Task 6 of SemEval-2021: Detection of Persuasion Techniques In Texts And Images, Subtask 1.
no code implementations • SEMEVAL 2021 • Anik Mondal, Raksha Sharma
This paper describes the system submitted to SemEval-2021 Task-7 for all four subtasks.
no code implementations • ACL 2018 • Raksha Sharma, Pushpak Bhattacharyya, D, S apat, ipan, Himanshu Sharad Bhatt
In this paper, we propose that words that do not change their polarity and significance represent the transferable (usable) information across domains for cross-domain sentiment classification.
no code implementations • EMNLP 2017 • Raksha Sharma, Arpan Somani, Lakshya Kumar, Pushpak Bhattacharyya
Identification of intensity ordering among polar (positive or negative) words which have the same semantics can lead to a fine-grained sentiment analysis.