Abstract
Detecting financial fraud is a daunting challenge for banks and credit card companies due to massive amount of transaction data and wide diversity of user behaviors [1]. In recent years social media has demonstrated the capability of crowdsourcing in a broad range of applications, e.g., disseminating breaking news, launching marketing campaigns, and tracking the flu [2], [3], [4]. Inspired by these novel applications, this paper explores the benefits of social media crowdsourcing, in particularly the tweets, re-tweets and comments from Twitter online social network for effectively detecting financial fraud events.
| Original language | English (US) |
|---|---|
| Title of host publication | 2014 IEEE 33rd International Performance Computing and Communications Conference, IPCCC 2014 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Volume | 2014-January |
| ISBN (Electronic) | 9781479975754 |
| DOIs | |
| State | Published - Jan 20 2015 |
| Event | 33rd IEEE International Performance Computing and Communications Conference, IPCCC 2014 - Austin, United States Duration: Dec 5 2014 → Dec 7 2014 |
Other
| Other | 33rd IEEE International Performance Computing and Communications Conference, IPCCC 2014 |
|---|---|
| Country | United States |
| City | Austin |
| Period | 12/5/14 → 12/7/14 |
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ASJC Scopus subject areas
- Software
- Computational Theory and Mathematics
- Computer Networks and Communications
Cite this
Financial fraud detection using social media crowdsourcing. / Matti, Timothy; Zhu, Yuntao; Xu, Kuai.
2014 IEEE 33rd International Performance Computing and Communications Conference, IPCCC 2014. Vol. 2014-January Institute of Electrical and Electronics Engineers Inc., 2015. 7017023.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Financial fraud detection using social media crowdsourcing
AU - Matti, Timothy
AU - Zhu, Yuntao
AU - Xu, Kuai
PY - 2015/1/20
Y1 - 2015/1/20
N2 - Detecting financial fraud is a daunting challenge for banks and credit card companies due to massive amount of transaction data and wide diversity of user behaviors [1]. In recent years social media has demonstrated the capability of crowdsourcing in a broad range of applications, e.g., disseminating breaking news, launching marketing campaigns, and tracking the flu [2], [3], [4]. Inspired by these novel applications, this paper explores the benefits of social media crowdsourcing, in particularly the tweets, re-tweets and comments from Twitter online social network for effectively detecting financial fraud events.
AB - Detecting financial fraud is a daunting challenge for banks and credit card companies due to massive amount of transaction data and wide diversity of user behaviors [1]. In recent years social media has demonstrated the capability of crowdsourcing in a broad range of applications, e.g., disseminating breaking news, launching marketing campaigns, and tracking the flu [2], [3], [4]. Inspired by these novel applications, this paper explores the benefits of social media crowdsourcing, in particularly the tweets, re-tweets and comments from Twitter online social network for effectively detecting financial fraud events.
UR - http://www.scopus.com/inward/record.url?scp=84983102478&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84983102478&partnerID=8YFLogxK
U2 - 10.1109/PCCC.2014.7017023
DO - 10.1109/PCCC.2014.7017023
M3 - Conference contribution
AN - SCOPUS:84983102478
VL - 2014-January
BT - 2014 IEEE 33rd International Performance Computing and Communications Conference, IPCCC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
ER -