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Reverse Engineering the Behaviour of Twitter Bots

Bello Shehu Bello, Reiko Heckel, Leandro Minku
2018 2018 Fifth International Conference on Social Networks Analysis, Management and Security (SNAMS)  
In 2015 DARPA organized the Twitter Bot Detection Challenge to developed techniques for early detection of bots [20] .  ...  We used Debot 13 , a system for the detection of Twitter bots to confirm our selection. For easy reference, we labelled the bots used in this paper as Bot1, Bot2 and Bot3.  ... 
doi:10.1109/snams.2018.8554675 dblp:conf/snams/BelloHM18 fatcat:wstcsyp6kzenxnbi3cx4xsnmbe

TweepFake: About detecting deepfake tweets

Tiziano Fagni, Fabrizio Falchi, Margherita Gambini, Antonio Martella, Maurizio Tesconi, Qingzhong Liu
2021 PLoS ONE  
It is real in the sense that each deepfake tweet was actually posted on Twitter. We collected tweets from a total of 23 bots, imitating 17 human accounts.  ...  However, to the best of our knowledge no one has ever addressed the detection of machine-generated texts on social networks like Twitter or Facebook.  ...  To have a better understanding on how the tested baselines behave at detection time, we split all available accounts on the dataset into four different categories: human The set of Twitter accounts having  ... 
doi:10.1371/journal.pone.0251415 pmid:33984021 fatcat:37wt7l2w3vdpdnr2udwj4fo7wu

SATAR: A Self-supervised Approach to Twitter Account Representation Learning and its Application in Bot Detection [article]

Shangbin Feng, Herun Wan, Ningnan Wang, Jundong Li, Minnan Luo
2021 arXiv   pre-print
To address the two challenges of Twitter bot detection, we propose SATAR, a self-supervised representation learning framework of Twitter users, and apply it to the task of bot detection.  ...  As a result, they fail to generalize to real-world scenarios on the Twittersphere where different types of bots co-exist. Additionally, bots in Twitter are constantly evolving to evade detection.  ...  In the following, we first review related work in Section 2 and define the task of Twitter bot detection in Section 3.  ... 
arXiv:2106.13089v2 fatcat:lybltfco6zfwlhednpb5upqn3u

A Deep Learning Approach for Robust Detection of Bots in Twitter using Transformers

David Martin-Gutierrez, Gustavo Hernandez Penaloza, Alberto Belmonte-Hernandez, Alicia Lozano-Diez, Federico Alvarez
2021 IEEE Access  
CONCLUSIONS & FUTURE WORK In this paper, a robust solution for detecting Bots in Twitter accounts has been described.  ...  In 2016, BotOrNot was proposed in [12] as a service to automatically detect bots in Twitter using similarities between characteristics of social bots.  ... 
doi:10.1109/access.2021.3068659 fatcat:mb646hcs7rdwbawxpuhvakffmq

Its all in a name: detecting and labeling bots by their name

David M. Beskow, Kathleen M. Carley
2018 Computational and mathematical organization theory  
To support this toolbox approach this research also uses random string detection applied to user names to filter twitter streams for bot accounts and use this as labeled training data for follow on research  ...  These efforts have resulted in a cat and mouse cycle in which detection algorithms evolve trying to keep up with ever evolving bots.  ...  Award W911NF1610049, Defense Threat Reductions Agency Award HDTRA11010102, and the Center for Computational Analysis of Social and Organization Systems (CASOS).  ... 
doi:10.1007/s10588-018-09290-1 fatcat:di3pfiw2hrge7caanqvu3rpyse

TweepFake: about Detecting Deepfake Tweets [article]

Tiziano Fagni, Fabrizio Falchi, Margherita Gambini, Antonio Martella, Maurizio Tesconi
2021 arXiv   pre-print
It is real in the sense that each deepfake tweet was actually posted on Twitter. We collected tweets from a total of 23 bots, imitating 17 human accounts.  ...  However, to the best of our knowledge no one has ever addressed the detection of machine-generated texts on social networks like Twitter or Facebook.  ...  To have a better understanding on how the tested baselines behave at detection time, we split all available accounts on the dataset into four different categories: human The set of Twitter accounts having  ... 
arXiv:2008.00036v2 fatcat:ljuernmicjckblwxdgraolwjy4

Bot stamina: examining the influence and staying power of bots in online social networks

Ross Schuchard, Andrew T. Crooks, Anthony Stefanidis, Arie Croitoru
2019 Applied Network Science  
We employ a methodological framework that aggregates and fuses data from multiple global Twitter conversations with an available bot detection platform and ultimately classifies the relative importance  ...  and persistence of social bots in online social networks (OSNs).  ...  Acknowledgements The authors would like to thank the DeBot team, led by Nikan Chavoshi, at the University of New Mexico for providing complete access to the DeBot platform bot archive.  ... 
doi:10.1007/s41109-019-0164-x fatcat:shda6ryryfbzfpxw7uaij5c2wu

Socialbots supporting human rights [article]

E. Velázquez, M. Yazdani, P. Suárez-Serrato
2017 arXiv   pre-print
We analyze the applicability of the BotOrNot API to generalize from English to Spanish tweets and propose adaptations for Spanish-speaking bot detection.  ...  Here we investigate the influence of socialbots in Mexican Twitter in regards to the "Tanhuato" human rights abuse report.  ...  We thank IPAM in UCLA and the organizers of the Cultural Analytics program, CNetS and the BotOrNot team in IU, and also Twitter for allowing access to data through their APIs.  ... 
arXiv:1710.11346v1 fatcat:jzb5jgg7tzejza4dt6lr2t43ry

Is this the Era of Misinformation yet

Patrick Wang, Rafael Angarita, Ilaria Renna
2018 Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18  
Social media is an amazing platform for enhancing public exposure. Anyone, even social bots, can reach out to a vast community and expose one's opinion.  ...  This paper reviews techniques that can be used to fabricate fake news and depicts a scenario where social bots evolve in a fully semantic Web to infest social media with automatically generated deceptive  ...  The third issue concerns the impossibility for social bots to detect and understand content that can be useful for their objectives.  ... 
doi:10.1145/3184558.3191610 dblp:conf/www/WangAR18 fatcat:2vjnvhieejfxxe7qkysbfuvd3e

Insights into elections: An ensemble bot detection coverage framework applied to the 2018 U.S. midterm elections

Ross J. Schuchard, Andrew T. Crooks, Sergio Gómez
2021 PLoS ONE  
Our findings suggest that social bot research efforts must incorporate multiple detection sources to account for the variety of social bots operating in OSNs, while incorporating improved or new detection  ...  This automated interaction proliferation within OSNs has led to the emergence of social bot detection efforts to better understand the extent and behavior of social bots.  ...  Acknowledgments A special thanks to the DeBot (New Mexico State University) and Bot-hunter research teams for providing access to their bot detection platforms to conduct this scaled analysis.  ... 
doi:10.1371/journal.pone.0244309 pmid:33406092 fatcat:4fs7lm5kojhf5c7vt7zgnerovm

Tracking Elections: our experience during the presidential elections in Ecuador [article]

Daniel Riofrio, Anacaren Ruiz, Erin Sosebee, Qasim Raza, Adnan Bashir, Jed Crandall
2018 arXiv   pre-print
Finally, we use bot detection systems and gathered more than 30,000 political motivated bots.  ...  In our data analysis, we show that these bots were mainly used for propaganda purposes in favor or against a particular candidate.  ...  We present the results of our Twitter analysis in two scenarios: candidate account analysis and bot detection analysis.  ... 
arXiv:1807.06147v1 fatcat:hupc7shrfrf37kd5kchxaspe2q

Detecting Propaganda on the Sentence Level during the COVID-19 Pandemic [article]

Rong-Ching Chang, Chu-Hsing Lin
2021 arXiv   pre-print
In this paper, using fine-tuned contextualized embedding trained on Reddit, we tackle the detection of the propaganda of such user accounts and their targeted issues on Twitter during March 2020 when the  ...  The pro-China group was also using more call-for-action words on political issues not necessarily China-related.  ...  In the future, we might consider using normalization mechanisms on a per-user basis. The Botometer is widely used in academia as a third-party validation for bot detection.  ... 
arXiv:2108.12269v1 fatcat:adf3efvawbe2zm7ax3fktdoz6i

The Doppelgänger Bot Attack

Oana Goga, Giridhari Venkatadri, Krishna P. Gummadi
2015 Proceedings of the 2015 ACM Conference on Internet Measurement Conference - IMC '15  
We also propose and evaluate methods to automatically detect impersonation attacks sooner than they are being detected in today's Twitter social network.  ...  One reason for the lack of studies in this space is the absence of datasets about impersonation attacks.  ...  Analyzing doppelgänger bot attacks In this section, our goal is to better understand doppelgänger bot attacks with the ultimate goal of detecting doppelgänger bots.  ... 
doi:10.1145/2815675.2815699 dblp:conf/imc/GogaVG15 fatcat:nu4qerf7lrao7lvyq3gdkivpai

Hello, Twitter Bot!: Towards a Bot Ethics of Response and Responsibility

Line Henriksen, Cancan Wang
2022 Catalyst Feminism Theory Technoscience  
We suggest that there is a tendency for bot ethics to revolve around the desire to differentiate between bot and human, which does not address what we understand to be the cultural anxieties at stake in  ...  bot creation, the Twitter bot "Hello30762308."  ...  in different but needed directions from the question of bot detection, to address what we argue is an Understanding Bot Creation: Discerning Benign and Deceptive Bots Bots are "(a)utomated or semi-automated  ... 
doi:10.28968/cftt.v8i1.36203 fatcat:5sxkvxd5hrgt5nwuko57squvrq

Identification of Twitter Bots Based on an Explainable Machine Learning Framework: The US 2020 Elections Case Study [article]

Alexander Shevtsov, Christos Tzagkarakis, Despoina Antonakaki, Sotiris Ioannidis
2021 arXiv   pre-print
Experimental evaluation on distinct Twitter datasets demonstrate the superiority of our approach, in terms of bot detection accuracy, when compared against a recent state-of-the-art Twitter bot detection  ...  This paper focuses on the design of a novel system for identifying Twitter bots based on labeled Twitter data.  ...  Acknowledgements We would like to thank the reviewers for their valuable comments.  ... 
arXiv:2112.04913v2 fatcat:y4w2aynj2jc5za4rbab5nt63m4
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