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Cashtag piggybacking: uncovering spam and bot activity in stock microblogs on Twitter [article]

Stefano Cresci, Fabrizio Lillo, Daniele Regoli, Serena Tardelli, Maurizio Tesconi
2018 arXiv   pre-print
Our results call for the adoption of spam and bot detection techniques in all studies and applications that exploit user-generated content for predicting the stock market.  ...  Yet, the presence (or lack thereof) and the impact of fake stock microblogs has never systematically been investigated before.  ...  To the best of our knowledge, this is the rst exploratory study on the presence of spam and bot activity in stock microblogs.  ... 
arXiv:1804.04406v2 fatcat:d4erx3svnrfkjpqt4tqlfdjeq4

FaNDS: Fake News Detection System Using Energy Flow [article]

Jiawei Xu, Vladimir Zadorozhny, Danchen Zhang, John Grant
2020 arXiv   pre-print
We present a new system, FaNDS, that detects fake news efficiently. The system is based on several concepts used in some previous works but in a different context.  ...  We compared FaNDS to several other fake news detection methods and found it to be more sensitive in discovering fake news items.  ...  According to the Financial Times, that one tweet caused a drop in the stock market with the S&P 500 declining 0.9% -enough to wipe out $130 billion in stock value in a matter of seconds [19] .  ... 
arXiv:2010.02097v1 fatcat:xbktpjiptfec5kt4xrg6ctp3cu

Spam Detection in Social Media using Machine Learning Algorithm

Yogita V Biyani
2021 International Journal for Research in Applied Science and Engineering Technology  
In this paper, tried to analyse various types of spamming attacks spam detection techniques, campaigns in Online Social site networks and information about spam detection.  ...  spammers has started spamming on these platforms for potential victims.  ...  A report by Nexgate estimates that on average one spam post occurs in every 200 social media posts and a more recent study reports that approximately 15% of active Twitter users are automated bots.  ... 
doi:10.22214/ijraset.2021.32832 fatcat:bbthheedingkpmgvm3jvylvazi

Reverse Engineering Socialbot Infiltration Strategies in Twitter [article]

Carlos A. Freitas, Fabrício Benevenuto, Saptarshi Ghosh, Adriano Veloso
2014 arXiv   pre-print
This study aims at understanding infiltration strategies of socialbots in the Twitter microblogging platform.  ...  group of users they interact with), and investigate the extent to which these bots are able to infiltrate the Twitter social network.  ...  Acknowledgements This work was supported by grants of CAPES, CNPq, and Fapemig.  ... 
arXiv:1405.4927v1 fatcat:o42doybkbrhdtny33zpar6tmry

Serf and Turf: Crowdturfing for Fun and Profit [article]

Gang Wang, Christo Wilson, Xiaohan Zhao, Yibo Zhu, Manish Mohanlal, Haitao Zheng, Ben Y. Zhao
2012 arXiv   pre-print
Finally, we study and compare the source of workers on crowdturfing sites in different countries.  ...  We analyze details of campaigns offered and performed in these sites, and evaluate their end-to-end effectiveness by running active, non-malicious campaigns of our own.  ...  Researchers have identified copious amounts of fake accounts and spam campaigns on large OSNs like Facebook [7] , Twitter [10, 31] , and Renren [33] .  ... 
arXiv:1111.5654v2 fatcat:dkayrgrqozbx3neb2oybf5kfsm

The Art of Social Bots: A Review and a Refined Taxonomy [article]

Majd Latah
2019 arXiv   pre-print
Malicious social bots were responsible for launching large-scale spam campaigns, promoting low-cap stocks, manipulating user's digital influence and conducting political astroturf.  ...  This paper presents a detailed review on current social bots and proper techniques that can be used to fly under the radar of OSNs defences to be undetectable for long periods of time.  ...  Acknowledgement We would like to thank Gonca Gürsun and Huseyin Ulusoy for their fruitful comments on the manuscript, which helped us improve the quality of this work.  ... 
arXiv:1905.03240v1 fatcat:a4bliz7dpvgy5aacvodamlaata

Social Botomics: A Systematic Ensemble ML Approach for Explainable and Multi-Class Bot Detection

Ilias Dimitriadis, Konstantinos Georgiou, Athena Vakali
2021 Applied Sciences  
Negative publicity on microblogging platforms, such as Twitter, is due to the infamous Twitter bots which highly impact posts' circulation and virality.  ...  Since, in an effort to win any war, it is critical to know your enemy, this work aims to demystify, reveal, and widen inherent characteristics of Twitter bots such that multiple types of bots are recognized  ...  Although Twitter itself has put a lot of effort into detecting and removing fake and bot accounts [24] [25] [26] , the issue still remains.  ... 
doi:10.3390/app11219857 doaj:d4f88d8e09204d8db15c09aa074c526f fatcat:dbhpkfwuhjfwnpph2escu6hipi

Deep learning for misinformation detection on online social networks: a survey and new perspectives

Md Rafiqul Islam, Shaowu Liu, Xianzhi Wang, Guandong Xu
2020 Social Network Analysis and Mining  
Therefore, related to the previous issues, we present a comprehensive survey of automated misinformation detection on (i) false information, (ii) rumors, (iii) spam, (iv) fake news, and (v) disinformation  ...  The existing studies have mainly focused on three broad categories of misinformation: false information, fake news, and rumor detection.  ...  Introduction On online social networks such as Facebook 1 , Twitter 2 , and Sina Weibo 3 , people share their opinions, videos, and news on their various activities (Gao and Liu 2014; Islam et al. 2018a  ... 
doi:10.1007/s13278-020-00696-x pmid:33014173 pmcid:PMC7524036 fatcat:473ziygl7jffbhwvpav3hlmppu

Risks and benefits of Twitter use by hematologists/oncologists in the era of digital medicine

Deanna J. Attai, Patricia F. Anderson, Michael J. Fisch, David L. Graham, Matthew S. Katz, Jennifer Kesselheim, Merry Jennifer Markham, Nathan A. Pennell, Mina S. Sedrak, Michael A. Thompson, Audun Utengen, Don S. Dizon
2017 Seminars in hematology (Print)  
Twitter use by physicians, including those in the hematology -oncology field, is increasing. This microblogging platform provides a means to communicate and collaborate on a global scale.  ...  The authors have summarized the benefits and risks of Twitter use by the hematology -oncology physician.  ...  "fake news"). There are a growing number of "bots" (automated "robot" accounts) that disseminate spam content [56] .  ... 
doi:10.1053/j.seminhematol.2017.08.001 pmid:29153081 pmcid:PMC5994350 fatcat:6qkxzayf6bgtzghx5zr2fygwxe

A comparative study of Bot Detection techniques methods with an application related to Covid-19 discourse on Twitter [article]

Marzia Antenore, Jose M. Camacho-Rodriguez, Emanuele Panizzi
2021 arXiv   pre-print
In order to address this issue, it has been compared different methods to detect automatically social bots on Twitter using Data Selection.  ...  In addition, it was analyzed the presence of bots in tweets from different periods of the first months of the Covid-19 pandemic, using the bot detection technique which best fits the scope of the task.  ...  [38] utilizes the former method to overcome a bot detection analysis over stock microblogs on Twitter. [55] and [65] present supervised models that uses Digital DNA.  ... 
arXiv:2102.01148v1 fatcat:n6ur2qtdfjek3gdplyiwjhqb3m

DeepTrust: A Reliable Financial Knowledge Retrieval Framework For Explaining Extreme Pricing Anomalies [article]

Pok Wah Chan
2022 arXiv   pre-print
The framework is evaluated on two self-annotated financial anomalies, i.e., Twitter and Facebook stock price on 29 and 30 April 2021.  ...  The optimal setup outperforms the baseline classifier by 7.75% and 15.77% on F0.5-scores, and 10.55% and 18.88% on precision, respectively, proving its capability in screening unreliable information precisely  ...  In addition, the abusive behavior on Twitter hashtags and cahstags has gradually become a common practice for bot-generated content to promote automated market updates or fake news, and is considered as  ... 
arXiv:2203.08144v1 fatcat:rusadj2rgrbplekl3bbpunbdwm

On the Wisdom of Experts vs. Crowds: Discovering Trustworthy Topical News in Microblogs

Muhammad Bilal Zafar, Parantapa Bhattacharya, Niloy Ganguly, Saptarshi Ghosh, Krishna P. Gummadi
2016 Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing - CSCW '16  
and ensuring trustworthiness of results in the face of spam.  ...  Extracting news on specific topics from the Twitter microblogging site poses formidable challenges, which include handling millions of tweets posted daily, judging topicality and importance of tweets,  ...  This research was supported in part by a grant from the Indo-German Max Planck Centre for Computer Science (IMPECS). Additionally, P.  ... 
doi:10.1145/2818048.2819968 dblp:conf/cscw/ZafarBGGG16 fatcat:4zlgagiv45ftbb7ujcsjdwygta

False News On Social Media: A Data-Driven Survey [article]

Francesco Pierri, Stefano Ceri
2020 arXiv   pre-print
The aim of this survey is to offer a comprehensive study on the recent advances in terms of detection, characterization and mitigation of false news that propagate on social media, as well as the challenges  ...  We use a data-driven approach, focusing on a classification of the features that are used in each study to characterize false information and on the datasets used for instructing classification methods  ...  They aim to find evidence of the considerable role of social bots in spreading lowcredibility news articles.  ... 
arXiv:1902.07539v3 fatcat:nfdrmyadnvgozhdfciap3krowy

#IStandWithDan versus #DictatorDan: the polarised dynamics of Twitter discussions about Victoria's COVID-19 restrictions

Timothy Graham, Axel Bruns, Daniel Angus, Edward Hurcombe, Sam Hames
2020 Media International Australia: Incorporating Culture & Policy  
a small number of hyper-partisan pro- and anti-government campaigners were able to mobilise ad hoc communities on Twitter, andin the case of the anti-government hashtag campaign – co-opt journalists  ...  dynamics of Twitter and the broader media and political establishment to progress their hyper-partisan agendas, and the utility of mixed-method approaches in helping render the dynamics of such campaigns  ...  to what extent, there is evidence of bot activity in these discussions, and how this varies between the hashtags.  ... 
doi:10.1177/1329878x20981780 fatcat:hr55gseeprahjcg5smt6bo26fm

Social Spammer Detection with Sentiment Information

Xia Hu, Jiliang Tang, Huiji Gao, Huan Liu
2014 2014 IEEE International Conference on Data Mining  
They collude with each other to imitate normal users by quickly accumulating a large number of "human" friends. In addition, content information in social media is noisy and unstructured.  ...  Experimental results on real-world social media datasets show the superior performance of the proposed framework by harnessing sentiment analysis for social spammer detection.  ...  [47] proposed to measure the dynamic sentiments on Twitter, and compared the correlation between public sentiments and major events, including the stock market, crude oil prices, elections and Thanksgiving  ... 
doi:10.1109/icdm.2014.141 dblp:conf/icdm/HuTGL14 fatcat:cbdgwsomindhpk2uuhlsyziwym
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