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Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
CoAID+: ¼Ò¼È ÄÁÅؽºÆ® ±â¹Ý °¡Â¥´º½º ŽÁö¸¦ À§ÇÑ COVID-19 ´º½º ÆÄ±Þ µ¥ÀÌÅÍ |
¿µ¹®Á¦¸ñ(English Title) |
CoAID+: COVID-19 News Cascade Dataset for Social Context Based Fake News Detection |
ÀúÀÚ(Author) |
ÇѼÒÀº
°À±¼®
°íÀ±¿ë
¾ÈÁö¿ø
±èÀ¯½É
¿À¼º¼ö
¹ÚÈñÁø
±è»ó¿í
Soeun Han
Yoonsuk Kang
Yunyong Ko
Jeewon Ahn
Yushim Kim
Seongsoo Oh
Heejin Park
Sang-Wook Kim
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¿ø¹®¼ö·Ïó(Citation) |
VOL 11 NO. 04 PP. 0149 ~ 0156 (2022. 04) |
Çѱ۳»¿ë (Korean Abstract) |
ÃÖ±Ù Àü ¼¼°èÀûÀ¸·Î COVID-19ÀÌ À¯ÇàÇÏ´Â »óȲ ¼Ó¿¡¼ ÀÌ¿Í °ü·ÃµÈ °¡Â¥´º½º°¡ ½É°¢ÇÑ »çȸÀû È¥¶õÀ» ¾ß±âÇÏ°í ÀÖ´Ù. ÀÌ·¯ÇÑ ¹è°æ¿¡¼ °¡Â¥´º½º¸¦ Á¤È®ÇÏ°Ô Å½ÁöÇϱâ À§ÇØ, ´º½º°¡ ¼Ò¼È ¹Ìµð¾î¸¦ ÅëÇØ Æı޵Ǵ °úÁ¤°ú °°Àº ¼Ò¼È ÄÁÅؽºÆ® Á¤º¸¸¦ È°¿ëÇÏ´Â ¼Ò¼È ÄÁÅؽºÆ® ±â¹Ý ŽÁö ±â¹ýµéÀÌ ³Î¸® »ç¿ëµÇ°í ÀÖ´Ù. ±×·¯³ª ´ëºÎºÐÀÇ ±â ±¸ÃàµÈ °¡Â¥´º½º ŽÁö¸¦ À§ÇÑ µ¥ÀÌÅ͵éÀº ´º½º ÀÚüÀÇ ³»¿ë Á¤º¸ À§ÁÖ·Î ±¸¼ºµÇ¾î, ¼Ò¼È ÄÁÅؽºÆ® Á¤º¸¸¦ °ÅÀÇ Æ÷ÇÔÇÏÁö ¾Ê´Â´Ù. Áï, ÀÌ µ¥ÀÌÅ͵鿡´Â ¼Ò¼È ÄÁÅؽºÆ® ±â¹Ý ŽÁö ±â¹ýÀ» Àû¿ëÇÒ ¼ö ¾øÀ¸¸ç, ÀÌ·¯ÇÑ µ¥ÀÌÅÍÀÇ ÇÑ°è´Â °¡Â¥´º½º ŽÁö ¿¬±¸ ºÐ¾ßÀÇ ¹ßÀüÀ» ÀúÇØÇÏ´Â ¹æÇØ ¿ä¼ÒÀÌ´Ù. º» ³í¹®Àº ÀÌ·¯ÇÑ ÇѰ踦 ±Øº¹Çϱâ À§ÇØ, ±âÁ¸ÀÇ Àú¸íÇÑ °¡Â¥´º½º µ¥ÀÌÅÍÀÎ CoAID µ¥ÀÌÅ͸¦ ±â¹ÝÀ¸·Î, ¼Ò¼È ÄÁÅؽºÆ® Á¤º¸¸¦ Ãß°¡ÀûÀ¸·Î ¼öÁýÇÏ¿©, CoAID µ¥ÀÌÅÍÀÇ ´º½º ³»¿ë Á¤º¸¿Í ÇØ´ç ´º½ºµéÀÇ ¼Ò¼È ÄÁÅؽºÆ® Á¤º¸¸¦ ¸ðµÎ Æ÷ÇÔÇÏ´Â CoAID+ µ¥ÀÌÅ͸¦ ±¸ÃàÇÑ´Ù. º» ³í¹®¿¡¼ ±¸ÃàÇÑ CoAID+ µ¥ÀÌÅÍ´Â ±âÁ¸ÀÇ ´ëºÎºÐÀÇ ¼Ò¼È ÄÁÅؽºÆ® ±â¹Ý ŽÁö ±â¹ýµé¿¡ Àû¿ëµÉ ¼ö ÀÖÀ¸¸ç, ÇâÈÄ »õ·Î¿î ¼Ò¼È ÄÁÅؽºÆ® ±â¹Ý ŽÁö ±â¹ýµé¿¡ ´ëÇÑ ¿¬±¸µµ ´õ¿í È°¼ºÈ½Ãų ¼ö ÀÖÀ» °ÍÀ¸·Î ±â´ëµÈ´Ù. ¸¶Áö¸·À¸·Î, º» ³í¹®Àº ´Ù¾çÇÑ °üÁ¡¿¡¼ CoAID+ µ¥ÀÌÅ͸¦ ºÐ¼®ÇÏ¿© ÁøÂ¥´º½º¿Í °¡Â¥´º½ºÀÇ ÆÄ±Þ ÆÐÅÏ ¹× Å°¿öµå¿¡ µû¸¥ ÆÄ±Þ ÆÐÅϵµ ÆľÇÇÏ¿© ¼Ò°³ÇÑ´Ù. |
¿µ¹®³»¿ë (English Abstract) |
In the current COVID-19 pandemic, fake news and misinformation related to COVID-19 have been causing serious confusion in our society. To accurately detect such fake news, social context-based methods have been widely studied in the literature. They detect fake news based on the social context that indicates how a news article is propagated over social media (e.g., Twitter). Most existing COVID-19 related datasets gathered for fake news detection, however, contain only the news content information, but not its social context information. In this case, the social context-based detection methods cannot be applied, which could be a big obstacle in the fake news detection research. To address this issue, in this work, we collect from Twitter the social context information based on CoAID, which is a COVID-19 news content dataset built for fake news detection, thereby building CoAID that includes both the news content information and its social context information. The CoAID dataset can be utilized in a variety of methods for social context-based fake news detection, thus would help revitalize the fake news detection research area. Finally, through a comprehensive analysis of the CoAID dataset in various perspectives, we present some interesting features capable of differentiating real and fake news. |
Å°¿öµå(Keyword) |
°¡Â¥´º½º ŽÁö
ÆıÞ
Äڷγª¹ÙÀÌ·¯½º
¼Ò¼È ÄÁÅؽºÆ® ±â¹Ý ŽÁö
Fake News Detection
Propagation
Coronavirus
Social Context Based Detection
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