TY - GEN
T1 - Analyzing disinformation and crowd manipulation tactics on youtube
AU - Hussain, Muhammad Nihal
AU - Tokdemir, Serpil
AU - Agarwal, Nitin
AU - Al-Khateeb, Samer
N1 - Funding Information:
ACKNOWLEDGEMENT This research is funded in part by the U.S. National Science Foundation (IIS-1636933, ACI-1429160, and IIS-1110868), U.S. Office of Naval Research (N00014-10-1-0091, N00014-14-1-0489, N00014-15-P-1187, N00014-16-1-2016, N00014-16-1-2412, N00014-17-1-2605, N00014-17-1-2675), U.S. Air Force Research Lab, U.S. Army Research Office (W911NF-16-1-0189), U.S. Defense Advanced Research Projects Agency (W31P4Q-17-C-0059), and the Jerry L. Maulden/Entergy Fund at the University of Arkansas at Little Rock.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/24
Y1 - 2018/10/24
N2 - YouTube, since its inception in 2005, has grown to become largest online video sharing website. It's massive userbase uploads videos and generates discussion by commenting on these videos. Lately, YouTube, akin to other social media sites, has become a vehicle for spreading fake news, propaganda, conspiracy theories, and radicalizing content. However, lack ineffective image and video processing techniques has hindered research on YouTube. In this paper, we advocate the use of metadata in identifying such malicious behaviors. Specifically, we analyze metadata of videos (e.g., comments, commenters) to study a channel on YouTube that was pushing content promoting conspiracy theories regarding World War III. Identifying signals that could be used to detect such deviant content (e.g., videos, comments) can help in stemming the spread of disinformation. We collected over 4,145 videos along with 16,493 comments from YouTube. We analyze user engagement to assess the reach of the channel and apply social network analysis techniques to identify inorganic behaviors.
AB - YouTube, since its inception in 2005, has grown to become largest online video sharing website. It's massive userbase uploads videos and generates discussion by commenting on these videos. Lately, YouTube, akin to other social media sites, has become a vehicle for spreading fake news, propaganda, conspiracy theories, and radicalizing content. However, lack ineffective image and video processing techniques has hindered research on YouTube. In this paper, we advocate the use of metadata in identifying such malicious behaviors. Specifically, we analyze metadata of videos (e.g., comments, commenters) to study a channel on YouTube that was pushing content promoting conspiracy theories regarding World War III. Identifying signals that could be used to detect such deviant content (e.g., videos, comments) can help in stemming the spread of disinformation. We collected over 4,145 videos along with 16,493 comments from YouTube. We analyze user engagement to assess the reach of the channel and apply social network analysis techniques to identify inorganic behaviors.
UR - http://www.scopus.com/inward/record.url?scp=85057341129&partnerID=8YFLogxK
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U2 - 10.1109/ASONAM.2018.8508766
DO - 10.1109/ASONAM.2018.8508766
M3 - Conference contribution
AN - SCOPUS:85057341129
T3 - Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018
SP - 1092
EP - 1095
BT - Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018
A2 - Tagarelli, Andrea
A2 - Reddy, Chandan
A2 - Brandes, Ulrik
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018
Y2 - 28 August 2018 through 31 August 2018
ER -