3 citations · 9 across the 11 of their papers we have counts for
11 papers
EquiSumm : A Gender Bias-Aware Framework for Inclusive Tweet Summarization
Chaitanya Wanjari, Jessica Kamal, Riddhi Jain +2
While social media platforms, such as Twitter, provide a medium for large-scale opinion sharing during news events, it is manually impossible for individuals or media agencies to p…
ADSumm: Annotated Ground-truth Summary Datasets for Disaster Tweet Summarization
Piyush Kumar Garg, Roshni Chakraborty, Sourav Kumar Dandapat
Online social media platforms, such as Twitter, provide valuable information during disaster events. Existing tweet disaster summarization approaches provide a summary of these eve…
ATSumm: Auxiliary information enhanced approach for abstractive disaster Tweet Summarization with sparse training data
Piyush Kumar Garg, Roshni Chakraborty, Sourav Kumar Dandapat
The abundance of situational information on Twitter poses a challenge for users to manually discern vital and relevant information during disasters. A concise and human-interpretab…
IKDSumm: Incorporating Key-phrases into BERT for extractive Disaster Tweet Summarization
Piyush Kumar Garg, Roshni Chakraborty, Srishti Gupta +1
Online social media platforms, such as Twitter, are one of the most valuable sources of information during disaster events. Therefore, humanitarian organizations, government agenci…
PORTRAIT: a hybrid aPproach tO cReate extractive ground-TRuth summAry for dIsaster evenT
Piyush Kumar Garg, Roshni Chakraborty, Sourav Kumar Dandapat
Disaster summarization approaches provide an overview of the important information posted during disaster events on social media platforms, such as, Twitter. However, the type of i…
EnDSUM: Entropy and Diversity based Disaster Tweet Summarization
Piyush Kumar Garg, Roshni Chakraborty, Sourav Kumar Dandapat
The huge amount of information shared in Twitter during disaster events are utilized by government agencies and humanitarian organizations to ensure quick crisis response and provi…
Finding Representative Sampling Subsets in Sensor Graphs using Time Series Similarities
Roshni Chakraborty, Josefine Holm, Torben Bach Pedersen +1
With the increasing use of IoT-enabled sensors, it is important to have effective methods for querying the sensors. For example, in a dense network of battery-driven temperature se…
Detecting Stance in Tweets : A Signed Network based Approach
Roshni Chakraborty, Maitry Bhavsar, Sourav Kumar Dandapat +1
Identifying user stance related to a political event has several applications, like determination of individual stance, shaping of public opinion, identifying popularity of governm…
SigGAN : Adversarial Model for Learning Signed Relationships in Networks
Roshni Chakraborty, Ritwika Das, Joydeep Chandra
Signed link prediction in graphs is an important problem that has applications in diverse domains. It is a binary classification problem that predicts whether an edge between a pai…
OntoDSumm : Ontology based Tweet Summarization for Disaster Events
Piyush Kumar Garg, Roshni Chakraborty, Sourav Kumar Dandapat
The huge popularity of social media platforms like Twitter attracts a large fraction of users to share real-time information and short situational messages during disasters. A summ…
Predicting Tomorrow's Headline using Today's Twitter Deliberations
Roshni Chakraborty, Abhijeet Kharat, Apalak Khatua +2
Predicting the popularity of news article is a challenging task. Existing literature mostly focused on article contents and polarity to predict popularity. However, existing resear…