22 citations · 40 across the 10 of their papers we have counts for
10 papers
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…
TONE: A 3-Tiered ONtology for Emotion analysis
Srishti Gupta, Piyush Kumar Garg, Sourav Kumar Dandapat
Emotions have played an important part in many sectors, including psychology, medicine, mental health, computer science, and so on, and categorizing them has proven extremely usefu…
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…
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…
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…
A Large-Scale Study of the Twitter Follower Network to Characterize the Spread of Prescription Drug Abuse Tweets
Ryan Sequeira, Avijit Gayen, Niloy Ganguly +2
In this article, we perform a large-scale study of the Twitter follower network, involving around 0.42 million users who justify DA, to characterize the spreading of DA tweets acro…
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…