Tutorial for SICSS-Istanbul. You can watch the video recording using this link.
data folder has all the datasets, network files, etc. One of the large tweet file uploaded to Zenodo platform. Click here to download
Onur Varol. (2020). SICSS - Tutorial Dataset File (Version v1.0.0) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3900655
notebooks has the code for the analysis in the form of IPython notebooks
figures folder has the images generated by Gephi or IPython notebooks
Title of Presentation: Identifying Networks of Social Bots on Twitter Conversations
Abstract of Presentation: In this tutorial, we will explore social media analysis concepts to identify automated entities, called social bots, on Twitter conversations. Hashtags loaded with suspicious intentions will be determined, and the Tweets containing that hashtags will be collected through Twitter API to identify (i) other co-occurring hashtags (ii) users posting Tweets with that hashtags and (iii) other meta-data captured from initial seed for further inspection. We identify the active and central users on the network using the social networks of the users and their activities. We will use Botometer API to measure bot-likely accounts and investigate their activities more closely. We investigate the properties of bot-likely accounts, the content they promote, and their social network composition. This tutorial aims to bring practical know-how on the tools and methodologies used in computational social science research.
Supplemantaries:
- Varol, Onur, and Ismail Uluturk. "Journalists on Twitter: self-branding, audiences, and involvement of bots." Journal of Computational Social Science (2019): 1-19. PDF
- Varol, O., Ferrara, E., Davis, C. A., Menczer, F., & Flammini, A. "Online human-bot interactions: Detection, estimation, and characterization" In Eleventh international AAAI conference on web and social media (2017) PDF
- Ferrara, E., Varol, O., Davis, C., Menczer, F., & Flammini, A. "The rise of social bots". Communications of the ACM (2016) 59(7), 96-104. PDF
- Varol, Onur, and Ismail Uluturk. "Deception strategies and threats for online discussions." First Monday (2018): 23-5. PDF
Speaker's Bio: Dr. Onur Varol is an Assistant Professor at the Sabanci University Faculty of Engineering and Natural Sciences and Principal Investigator at the VIRAL Lab. His research focuses on developing techniques to analyze online behaviors to improve individual well-being and address societal problems using online data. Prior to joining Sabanci University, he was a postdoctoral researcher at Northeastern University at the Center for Complex Network Research. He completed his PhD in Informatics at Indiana University, Bloomington (USA). His thesis focuses on the analysis of manipulation and threats on social media and he was awarded the 2018 University Distinguished Ph.D. Dissertation Award. He has developed a system called Botometer to detect social bots on Twitter and his team ranked top 3 worldwide at the 2015 DARPA Bot Detection Challenge. Efforts on studying social bots yield publications on prestigious venues such as International Conference of Web and Social Media (ICWSM), Nature Communications, World Wide Web (WWW) conference, and Communications of the ACM.