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Doğrulanmış Twitter Hesaplarının Karakteristiklerinin Analizi

Year 2019, Volume: 2 Issue: 3, 180 - 186, 31.12.2019

Abdullah Talha Kabakuş , Mehmet Şimşek

https://doi.org/10.35377/saucis.02.03.649708
Cited By: 3

Abstract

En popüler mikroblog olan Twitter, sahip olduğu devasa
popüleritenin sonucu olarak çok çeşitli kullanıcı kitlesine sahiptir. Twitter
kamu yararına olacağı inanılan hesapları elle doğrulamaktadır. Doğrulanmanın
doğal bir sonucu olarak kullanıcılar, bu hesapların meşru kullanıcıları temsil
etmesinden ve yetkili kullanıcılar tarafından yönetilmesinden dolayı bu
hesaplara güven duymaktadır. Elde ettiğimiz en iyi verilere göre, Twitter
doğrulanmanın gereksinimlerini hiçbir zaman açıklamamıştır. Bu çalışmada, doğrulanmış
kullanıcıların karakteristiklerine ışık tutmak amacıyla bu çalışma kapsamında Python
programlam dili tabanlı 297.798 doğrulanmış Twitter kullanıcısı içeren güncel
bir verisetini kullanan bir yazılım geliştirilmiştir. Bu veriseti üzerinde
yapılan analizler sonucunda doğrulanmış kullanıcıların kamuya açık olma,
kişiselleştirilmiş bir profile sahip olma gibi ortak karakteristikleri açığa
çıkartılmıştır.

Keywords

Twitter mikroblog sosyal medya analizi doğrulanmış kullanıcılar doğrulama

References

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An Analysis of the Characteristics of Verified Twitter Users

Year 2019, Volume: 2 Issue: 3, 180 - 186, 31.12.2019

Abdullah Talha Kabakuş , Mehmet Şimşek

https://doi.org/10.35377/saucis.02.03.649708
Cited By: 3

Abstract

Twitter, the
most popular microblog, contains a large variety of users as a result of its
huge popularity. Twitter manually verifies the accounts which are deemed worthy
of public interest. As a natural consequence of being verified, users trust these
verified accounts since they represent legitimate users, and are managed by
authorized users. To the best of our knowledge, Twitter has never revealed the
requirements of being verified. In this study, in order to shed light on the
characteristics of verified Twitter users, a software,
which is based on Python programming language that utilizes a recent
dataset, which consists of 297,798 verified Twitter users, was implemented
within the scope of this study. The characteristics of verified Twitter users such
as being public, and having a customized profile were revealed as a result of
the analysis of the utilized dataset.

Keywords

Twitter microblog social media analysis verified users verification

References

  • [1] “Q1 2019 Earnings Report,” Twitter, 2019. [Online]. Available: https://s22.q4cdn.com/826641620/files/doc_financials/2019/q1/Q1-2019-Slide-Presentation.pdf. [Accessed: 15-Nov-2019].
  • [2] “Agency Playbook,” Twitter, 2019. [Online]. Available: https://cdn.cms-twdigitalassets.com/content/dam/business-twitter/resources/Twitter_Agency_Playbook_2019.pdf. [Accessed: 15-Nov-2019].
  • [3] “2018 Twitter Report,” Mention, 2018. [Online]. Available: https://info.mention.com/hubfs/Twitter Engagement Report 2018 %7C Mention.pdf. [Accessed: 15-Nov-2019].
  • [4] A. Pak and P. Paroubek, “Twitter as a Corpus for Sentiment Analysis and Opinion Mining,” in Proceedings of LREC’10, the Seventh International Conference on Language Resources and Evaluation, 2010, pp. 1320–1326.
  • [5] S. Waisbord and A. Amado, “Populist communication by digital means: presidential Twitter in Latin America,” Inf. Commun. Soc., vol. 20, no. 9, pp. 1330–1346, 2017.
  • [6] H. Kwak, C. Lee, H. Park, and S. Moon, “What is Twitter, a social network or a news media?,” in Proceedings of the 19th International Conference on World Wide Web (WWW ’10), 2010, pp. 591–600.
  • [7] R. Li, K. H. Lei, R. Khadiwala, and K. C. C. Chang, “TEDAS: A twitter-based event detection and analysis system,” in Proceedings of the 2012 IEEE 28th International Conference on Data Engineering, 2012, pp. 1273–1276.
  • [8] I. Paul, A. Khattar, P. Kumaraguru, M. Gupta, and S. Chopra, “Elites Tweet? Characterizing the Twitter Verified User Network,” in Proceedings of the 2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW), 2019.
  • [9] M. Hentschel, O. Alonso, S. Counts, and V. Kandylas, “Finding Users We Trust: Scaling Up Verified Twitter Users Using Their Communication Patterns,” in Proceedings of the 8th International AAAI Conference on Weblogs and Social Media (ICWSM 2014), 2014, pp. 591–594.
  • [10] O. Varol, E. Ferrara, C. A. Davis, F. Menczer, and A. Flammini, “Online Human-Bot Interactions: Detection, Estimation, and Characterization,” in Proceedings of the 11th International Conference on Web and Social Media (ICWSM 2017), 2017.
  • [11] C. De Micheli and A. Stroppa, “Twitter and the underground market,” 2013. [Online]. Available: https://nexa.polito.it/nexacenterfiles/lunch-11-de_micheli-stroppa.pdf. [Accessed: 16-Nov-2019].
  • [12] Y. Roth and D. Harvey, “How Twitter is fighting spam and malicious automation,” Twitter, 2018. [Online]. Available: https://blog.twitter.com/en_us/topics/company/2018/how-twitter-is-fighting-spam-and-malicious-automation.html. [Accessed: 16-Nov-2019].
  • [13] H. L. LaMarre and Y. Suzuki-Lambrecht, “Tweeting democracy? Examining Twitter as an online public relations strategy for congressional campaigns’,” Public Relat. Rev., vol. 39, no. 4, pp. 360–368, 2013.
  • [14] Jason Baumgartner, “All Verified Twitter Users (100% complete) in ndjson format : datasets,” pushshift.io, 2018. [Online]. Available: https://www.reddit.com/r/datasets/comments/8s6nqz/all_verified_twitter_users_100_complete_in_ndjson/. [Accessed: 15-Nov-2019].
  • [15] “API reference index — Twitter Developers,” Twitter, 2019. [Online]. Available: https://developer.twitter.com/en/docs/api-reference-index. [Accessed: 15-Nov-2019].
  • [16] B. Erşahin, Ö. Aktaş, D. Kilmç, and C. Akyol, “Twitter fake account detection,” in 2nd International Conference on Computer Science and Engineering (UBMK 2017), 2017, pp. 388–392.
  • [17] “pandas: Python Data Analysis Library,” 2019. [Online]. Available: https://pandas.pydata.org. [Accessed: 16-Nov-2019].
  • [18] “Matplotlib: Python plotting — Matplotlib 3.1.1 documentation,” 2019. [Online]. Available: https://matplotlib.org. [Accessed: 16-Nov-2019].
  • [19] T. Velayutham and P. K. Tiwari, “Bot Identification: Helping Analysts for Right Data in Twitter,” in Proceedings - 2017 3rd International Conference on Advances in Computing, Communication and Automation (Fall) (ICACCA 2017), 2018, pp. 1–5.
  • [20] S. Yardi, D. Romero, G. Schoenebeck, and D. Boyd, “Detecting spam in a Twitter network,” First Monday, vol. 15, no. 1, 2010.
There are 20 citations in total.

Details

Primary Language English
Subjects Computer Software
Journal Section Articles
Authors

Abdullah Talha Kabakuş 0000-0003-2181-4292

Mehmet Şimşek 0000-0002-9797-5028

Publication Date December 31, 2019
Submission Date November 21, 2019
Acceptance Date December 30, 2019
Published in Issue Year 2019Volume: 2 Issue: 3

Cite

IEEE A. T. Kabakuş and M. Şimşek, “An Analysis of the Characteristics of Verified Twitter Users”, SAUCIS, vol. 2, no. 3, pp. 180–186, 2019, doi: 10.35377/saucis.02.03.649708.

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