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An Analysis of Slant in Tweets: Case Study

Published: 02 December 2019 Publication History

Abstract

Determination of quality and reliability of information found in social media have been subjects of study by sever researchers. One set of solution may not work in all cases. This paper presents a method to estimate the slant of tweets related to a topic. The general approach followed is to construct labeled data from tweets and use supervised learning to build predictive models. Results obtained from two datasets are compared against OTC model and a CNN based model.

References

[1]
James C. Bezdek, Robert Ehrlich, and William Full, "FCM: The Fuzzy C-Means Clustering Algorithm", Computers & Geosciences, Vol. 10, No. 2--3, 1984, pp. 191--203.
[2]
Yi-Chin Chen, Zhao-Yang Liu, Hung-Yu Kao, "IKM at SemEval-2017 Task 8: Convolutional Neural Networks for Stance Detection and Rumor Verification", Proceedings of the 11th International Workshop on Semantic Evaluations (SemEval-2017), Vancouver, Canada, August 3 - 4, 2017, pp. 465--469.
[3]
G. Giasemidis, et al. (2016) Determining the Veracity of Rumours on Twitter. In: Spiro E., Ahn YY. (eds) Social Informatics. SocInfo 2016. Lecture Notes in Computer Science, vol 10046. Springer, Cham, pp. 185--205.
[4]
Nicolas Gillis, "The Why and How of Nonnegative Matrix Factorization", arXiv:1401.5226v2, Mar 2014.
[5]
Sunita Goel and Ozlem Uzuner, "Do Sentiments Matter in Fraud Detection? Estimating Semantic Orientation of Annual Reports", Intelligent Systems in Accounting, Finance and Management, Volume 23, Issue 3, Special Issue in Accounting, Auditing and Finance Applications, July/September 2016, pp. 155--254
[6]
Sejeong Kwon, Meeyoung Cha, Kyomin Jung, Wei Chen, and Yajun Wang "Prominent features of rumor propagation in online social media", Proceedings of the 2013 IEEE 13th International Conference on Data Mining, IEEE, 2013, pp. 1103--11083.
[7]
Daniel D. Lee and H. Sebastian Seung, "Algorithms for non-negative matrix factorization", Proceedings of the 13th International Conference on Neural Information Processing Systems, Denver, CO, 2000, pp. 535--541.
[8]
Tatiana Lukoianova and Victoria L. Rubin, "Veracity Roadmap: Is Big Data Objective, Truthful and Credible?", Advances In Classification Research Online, 24(1).
[9]
Tu Ngoc Nguyen, Cheng Li, and Claudia Niederée, "On Early-Stage Debunking Rumors on Twitter: Leveraging the Wisdom of Weak Learners", Proceedings of the Social Informatics: 9th International Conference, SocInfo 2017, Part 2, pp. 141--158.
[10]
C. E. Shannon, "A Mathematical Theory of Communication", The Bell System Technical Journal, Volume 27, Issue 3, July 1948, pp. 379--423.
[11]
Arkaitz Zubiaga, Ahmet Aker, Kalina Bontcheva, Maria Liakata, and Rob Procter, "Detection and Resolution of Rumours in Social Media: A Survey", ACM Computing Surveys, Vol. 51, No.2, February 2018, pp. 32:1--32:36, https://doi.org/10.1145/3161603.
[12]
https://www.statista.com/statistics/282087/number-of-monthly-active-twitter-users/
[13]
https://www.nytimes.com/2017/10/30/technology/facebook-google-russia.html
[14]
Nadeem Ahmad and Jawaid Siddique, "Personality Assessment using Twitter Tweets", Proceedings of the 21st International Conference on Knowledge Based and Intelligent Information and Engineering Systems, KES2017,6--8 September 2017.

Cited By

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  • (2024)Gender classification of product reviewers in China: a data-driven approachInformation Technology and Management10.1007/s10799-024-00443-0Online publication date: 20-Nov-2024
  • (2021)Detecting Propaganda in Trending Twitter Topics in India—A Metric Driven ApproachEmerging Technologies in Data Mining and Information Security10.1007/978-981-33-4367-2_62(657-671)Online publication date: 5-May-2021

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cover image ACM Conferences
BDCAT '19: Proceedings of the 6th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies
December 2019
174 pages
ISBN:9781450370165
DOI:10.1145/3365109
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 ACM 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]

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Publication History

Published: 02 December 2019

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Author Tags

  1. bias
  2. clustering
  3. neural network
  4. prediction
  5. sentiment analysis
  6. tweets
  7. veracity

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Overall Acceptance Rate 27 of 93 submissions, 29%

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Cited By

View all
  • (2024)Gender classification of product reviewers in China: a data-driven approachInformation Technology and Management10.1007/s10799-024-00443-0Online publication date: 20-Nov-2024
  • (2021)Detecting Propaganda in Trending Twitter Topics in India—A Metric Driven ApproachEmerging Technologies in Data Mining and Information Security10.1007/978-981-33-4367-2_62(657-671)Online publication date: 5-May-2021

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