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Reverse Engineering the Behaviour of Twitter Bots
2018
2018 Fifth International Conference on Social Networks Analysis, Management and Security (SNAMS)
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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
2021
PLoS ONE
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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]
2021
arXiv
pre-print
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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
2021
IEEE Access
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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
2018
Computational and mathematical organization theory
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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]
2021
arXiv
pre-print
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2020 pre-print arXiv:2008.00036v1 fatcat:liwhnem5nnbbhhcw7ozv6wzoba
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
2019
Applied Network Science
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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]
2017
arXiv
pre-print
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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
2018
Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18
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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
2021
PLoS ONE
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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]
2018
arXiv
pre-print
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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]
2021
arXiv
pre-print
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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
2015
Proceedings of the 2015 ACM Conference on Internet Measurement Conference - IMC '15
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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
2022
Catalyst Feminism Theory Technoscience
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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]
2021
arXiv
pre-print
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2021 pre-print arXiv:2112.04913v1 fatcat:rywly75sxvf5vjgspgsv7dm6mu
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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