Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox
Picture for Kunwoo Park

Kunwoo Park

How does fake news use a thumbnail? CLIP-based Multimodal Detection on the Unrepresentative News Image


Apr 27, 2022
Hyewon Choi, Yejun Yoon, Seunghyun Yoon, Kunwoo Park

Figure 1 for How does fake news use a thumbnail? CLIP-based Multimodal Detection on the Unrepresentative News Image
Figure 2 for How does fake news use a thumbnail? CLIP-based Multimodal Detection on the Unrepresentative News Image
Figure 3 for How does fake news use a thumbnail? CLIP-based Multimodal Detection on the Unrepresentative News Image
Figure 4 for How does fake news use a thumbnail? CLIP-based Multimodal Detection on the Unrepresentative News Image
* 9 pages, 8 figures including appendix figure, 2 tables. Published in Findings of ACL workshop, CONSTRAINT 2022 (Long paper). The manuscript is slightly revised after the camera ready version 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Who Is Missing? Characterizing the Participation of Different Demographic Groups in a Korean Nationwide Daily Conversation Corpus


Apr 20, 2022
Haewoon Kwak, Jisun An, Kunwoo Park

Figure 1 for Who Is Missing? Characterizing the Participation of Different Demographic Groups in a Korean Nationwide Daily Conversation Corpus
Figure 2 for Who Is Missing? Characterizing the Participation of Different Demographic Groups in a Korean Nationwide Daily Conversation Corpus
Figure 3 for Who Is Missing? Characterizing the Participation of Different Demographic Groups in a Korean Nationwide Daily Conversation Corpus
Figure 4 for Who Is Missing? Characterizing the Participation of Different Demographic Groups in a Korean Nationwide Daily Conversation Corpus
* Accepted in AAAI ICWSM'22 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Who Blames or Endorses Whom? Entity-to-Entity Directed Sentiment Extraction in News Text


Jun 22, 2021
Kunwoo Park, Zhufeng Pan, Jungseock Joo

Figure 1 for Who Blames or Endorses Whom? Entity-to-Entity Directed Sentiment Extraction in News Text
Figure 2 for Who Blames or Endorses Whom? Entity-to-Entity Directed Sentiment Extraction in News Text
Figure 3 for Who Blames or Endorses Whom? Entity-to-Entity Directed Sentiment Extraction in News Text
Figure 4 for Who Blames or Endorses Whom? Entity-to-Entity Directed Sentiment Extraction in News Text
* Published in Findings of ACL 2021 (Long paper). The manuscript is slightly revised after the camera ready version 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Understanding Effects of Editing Tweets for News Sharing by Media Accounts through a Causal Inference Framework


Sep 17, 2020
Kunwoo Park, Haewoon Kwak, Jisun An, Sanjay Chawla

Figure 1 for Understanding Effects of Editing Tweets for News Sharing by Media Accounts through a Causal Inference Framework
Figure 2 for Understanding Effects of Editing Tweets for News Sharing by Media Accounts through a Causal Inference Framework
Figure 3 for Understanding Effects of Editing Tweets for News Sharing by Media Accounts through a Causal Inference Framework
Figure 4 for Understanding Effects of Editing Tweets for News Sharing by Media Accounts through a Causal Inference Framework
* 12 pages, 5 figures. To appear at ICWSM'21 as full paper 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

BaitWatcher: A lightweight web interface for the detection of incongruent news headlines


Mar 23, 2020
Kunwoo Park, Taegyun Kim, Seunghyun Yoon, Meeyoung Cha, Kyomin Jung

Figure 1 for BaitWatcher: A lightweight web interface for the detection of incongruent news headlines
Figure 2 for BaitWatcher: A lightweight web interface for the detection of incongruent news headlines
Figure 3 for BaitWatcher: A lightweight web interface for the detection of incongruent news headlines
Figure 4 for BaitWatcher: A lightweight web interface for the detection of incongruent news headlines
* 24 pages (single column), 7 figures. This research article is published as a book chapter of \textit{Fake News, Disinformation, and Misinformation in Social Media-Emerging Research Challenges and Opportunities}. Springer, 2020. arXiv admin note: text overlap with arXiv:1811.07066 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Detecting Incongruity Between News Headline and Body Text via a Deep Hierarchical Encoder


Nov 17, 2018
Seunghyun Yoon, Kunwoo Park, Joongbo Shin, Hongjun Lim, Seungpil Won, Meeyoung Cha, Kyomin Jung

Figure 1 for Detecting Incongruity Between News Headline and Body Text via a Deep Hierarchical Encoder
Figure 2 for Detecting Incongruity Between News Headline and Body Text via a Deep Hierarchical Encoder
Figure 3 for Detecting Incongruity Between News Headline and Body Text via a Deep Hierarchical Encoder
Figure 4 for Detecting Incongruity Between News Headline and Body Text via a Deep Hierarchical Encoder
* 10 pages, Accepted as a conference paper at AAAI 2019 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email