TY - GEN
T1 - Analyzing social and communication network structures of social bots and humans
AU - Khaund, Tuja
AU - Bandeli, Kiran Kumar
AU - Hussain, Muhammad Nihal
AU - Obadimu, Adewale
AU - Al-Khateeb, Samer
AU - Agarwal, Nitin
N1 - Funding Information:
This research is funded in part by the U.S. National Science, U.S. Office of Naval, U.S. Air Force Research Lab, U.S. Army Research, U.S. Defense Advanced Research Projects Agency and the Jerry L. Maulden/Entergy Endowment at the University of Arkansas at Little Rock.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/24
Y1 - 2018/10/24
N2 - Recently, several journalistic accounts have suggested that Twitter is becoming a bellwether for mis- and disinformation due to the pervasiveness of bots. These bots are either automated or semi-automated. Understanding the intent and usage of these bots has piqued the scientific curiosity among researchers. To that effect, in this study, we analyze the role of bots in two distinct categories of real-world events, i.e., natural disasters and sports. We collected over 1.2 million tweets that were generated by nearly 800,000 users for Hurricane Harvey, Hurricane Irma, Hurricane Maria, and Mexico Earthquake. We corroborate our analysis by examining bots that engaged with the 2018 Winter Olympics. We collected over 1.4 million tweets generated by nearly 700,000 users based on the hashtags #Olympics2018 and #PyeongChang2018. We examined the social and communication network of bots and humans for the aforementioned events. Our results show distinctive patterns in the network structures of bots when compared with that of humans. Content analysis of the tweets further revealed that bots used hashtags more uniformly than humans, across all the events.
AB - Recently, several journalistic accounts have suggested that Twitter is becoming a bellwether for mis- and disinformation due to the pervasiveness of bots. These bots are either automated or semi-automated. Understanding the intent and usage of these bots has piqued the scientific curiosity among researchers. To that effect, in this study, we analyze the role of bots in two distinct categories of real-world events, i.e., natural disasters and sports. We collected over 1.2 million tweets that were generated by nearly 800,000 users for Hurricane Harvey, Hurricane Irma, Hurricane Maria, and Mexico Earthquake. We corroborate our analysis by examining bots that engaged with the 2018 Winter Olympics. We collected over 1.4 million tweets generated by nearly 700,000 users based on the hashtags #Olympics2018 and #PyeongChang2018. We examined the social and communication network of bots and humans for the aforementioned events. Our results show distinctive patterns in the network structures of bots when compared with that of humans. Content analysis of the tweets further revealed that bots used hashtags more uniformly than humans, across all the events.
UR - http://www.scopus.com/inward/record.url?scp=85057341778&partnerID=8YFLogxK
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U2 - 10.1109/ASONAM.2018.8508665
DO - 10.1109/ASONAM.2018.8508665
M3 - Conference contribution
AN - SCOPUS:85057341778
T3 - Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018
SP - 794
EP - 797
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 -