skip to main content
10.1145/3011141.3011199acmotherconferencesArticle/Chapter ViewAbstractPublication PagesiiwasConference Proceedingsconference-collections
short-paper

Applying a tendency to be well retweeted to false information detection

Published: 28 November 2016 Publication History

Abstract

While a lot of useful information can be found in SNS, false information also diffuses through it, thereby confusing many people sometimes. In this paper, we predict a tendency of tweets to be well retweeted and consider applying the tendency to false information detection. The tendency prediction can be implemented with simple features of tweets. We examine the effect of the tendency when it is used in false information detection empirically. Our experimental results indicate that it would be valuable to take the tendency into account for the detection. We also discuss findings when applying them to tweets in Japanese.

References

[1]
E. F. Can, H. Oktay, and R. Manmatha. Predicting retweet count using visual cues. In Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, CIKM '13, pages 1481--1484, New York, NY, USA, 2013. ACM.
[2]
C. Castillo, M. Mendoza, and B. Poblete. Information credibility on twitter. In Proceedings of the 20th International Conference on World Wide Web, WWW '11, pages 675--684, New York, NY, USA, 2011. ACM.
[3]
A. Gupta and P. Kumaraguru. Credibility ranking of tweets during high impact events. In Proceedings of the 1st Workshop on Privacy and Security in Online Social Media, PSOSM '12, pages 2:2--2:8, New York, NY, USA, 2012. ACM.
[4]
A. Gupta, H. Lamba, and P. Kumaraguru. $1.00 per rt #bostonmarathon #prayforboston: analyzing fake content on twitter. In eCrime Research Summit. http://precog.iiitd.edu.in/Publications_files/ecrs2013_ag_hl_pk.pdf, Sept. 2013.
[5]
J. Ma, W. Gao, Z. Wei, Y. Lu, and K.-F. Wong. Detect rumors using time series of social context information on microblogging websites. In Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, CIKM '15, pages 1751--1754, New York, NY, USA, 2015. ACM.
[6]
M. Mathioudakis and N. Koudas. Twittermonitor: Trend detection over the twitter stream. In Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data, SIGMOD '10, pages 1155--1158, New York, NY, USA, 2010. ACM.
[7]
A. Nadamoto, M. Miyabe, and E. Aramaki. Analysis of microblog rumors and correction texts for disaster situations. In Proceedings of International Conference on Information Integration and Web-based Applications & Services, IIWAS '13, pages 44:44--44:52, New York, NY, USA, 2013. ACM.
[8]
A. Umejima, M. Miyabe, E. Aramaki, and A. Nadamoto. Tendency of rumor and correction re-tweet on the twitter during disasters (in Japanese). Technical Report http://id.nii.ac.jp/1001/00075459/, IPSJ SIG Technical Reports, July 2011.
[9]
Y. Yasuda. Information dissemination in social media: Hubs and demagogues (in Japanese). Technical Report http://hdl.handle.net/10112/8399, Kansai University, Dec. 2013.
[10]
Z. Yoshida and M. Aritsugi. Rumor detection using tendencies to be well retweeted (in Japanese). Technical Report http://db-event.jpn.org/deim2016/papers/351.pdf, DEIM Forum, Mar. 2016.
[11]
Y. Yoshitsugu. Roles of social media at the time of major disasters observed in the great east japan earthquake: Twitter as an example (in Japanese). Technical Report http://www.nhk.or.jp/bunken/english/reports/summary/201107/02.html, NHK Broadcasting Culture Research Institute, July 2011.
[12]
Z. Zhao, P. Resnick, and Q. Mei. Enquiring minds: Early detection of rumors in social media from enquiry posts. In Proceedings of the 24th International Conference on World Wide Web, WWW '15, pages 1395--1405, New York, NY, USA, 2015. ACM.

Cited By

View all
  • (2022)Estimating the Best Time to View Cherry Blossoms Using Time-Series Forecasting MethodMachine Learning and Knowledge Extraction10.3390/make40200184:2(418-431)Online publication date: 30-Apr-2022
  • (2020)Socio-Technical Mitigation Effort to Combat Cyber Propaganda: A Systematic Literature MappingIEEE Access10.1109/ACCESS.2020.29946588(92929-92944)Online publication date: 2020
  • (2018)Rumor Detection in Twitter with Social Graph StructuresThird International Congress on Information and Communication Technology10.1007/978-981-13-1165-9_54(589-598)Online publication date: 29-Sep-2018

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
iiWAS '16: Proceedings of the 18th International Conference on Information Integration and Web-based Applications and Services
November 2016
528 pages
ISBN:9781450348072
DOI:10.1145/3011141
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 November 2016

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. SNS
  2. Twitter
  3. false rumors
  4. information credibility

Qualifiers

  • Short-paper

Conference

iiWAS '16

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)1
  • Downloads (Last 6 weeks)0
Reflects downloads up to 22 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2022)Estimating the Best Time to View Cherry Blossoms Using Time-Series Forecasting MethodMachine Learning and Knowledge Extraction10.3390/make40200184:2(418-431)Online publication date: 30-Apr-2022
  • (2020)Socio-Technical Mitigation Effort to Combat Cyber Propaganda: A Systematic Literature MappingIEEE Access10.1109/ACCESS.2020.29946588(92929-92944)Online publication date: 2020
  • (2018)Rumor Detection in Twitter with Social Graph StructuresThird International Congress on Information and Communication Technology10.1007/978-981-13-1165-9_54(589-598)Online publication date: 29-Sep-2018

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media