Charting the Landscape of Online Cryptocurrency Manipulation
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Maurizio Tesconi | Emilio Ferrara | Marco Avvenuti | Stefano Cresci | Serena Tardelli | Leonardo Nizzoli | Emilio Ferrara | M. Tesconi | M. Avvenuti | S. Cresci | S. Tardelli | Leonardo Nizzoli
[1] Jaewook Lee,et al. An Empirical Study on Modeling and Prediction of Bitcoin Prices With Bayesian Neural Networks Based on Blockchain Information , 2018, IEEE Access.
[2] Kristina Lerman,et al. Linguistic Cues to Deception: Identifying Political Trolls on Social Media , 2019, ICWSM.
[3] Maurizio Tesconi,et al. RTbust: Exploiting Temporal Patterns for Botnet Detection on Twitter , 2019, WebSci.
[4] Sebastian Stier,et al. How to Manipulate Social Media: Analyzing Political Astroturfing Using Ground Truth Data from South Korea , 2017, ICWSM.
[5] John Nelson,et al. Cryptocurrency Price Prediction Using Tweet Volumes and Sentiment Analysis , 2018 .
[6] Samuel C. Woolley,et al. Automating power: Social bot interference in global politics , 2016, First Monday.
[7] Neil Gandal,et al. An Examination of the Cryptocurrency Pump and Dump Ecosystem , 2018, Inf. Process. Manag..
[8] P. Erdos,et al. On the evolution of random graphs , 1984 .
[9] Emilio Ferrara,et al. Bots increase exposure to negative and inflammatory content in online social systems , 2018, Proceedings of the National Academy of Sciences.
[10] Mike Thelwall,et al. Can social news websites pay for content and curation? The SteemIt cryptocurrency model , 2018, J. Inf. Sci..
[11] Marco Linton,et al. Dynamic Topic Modelling for Cryptocurrency Community Forums , 2016 .
[12] Jan Eloff,et al. Using Machine Learning to Detect Fake Identities: Bots vs Humans , 2018, IEEE Access.
[13] Hossein Hamooni,et al. DeBot: Twitter Bot Detection via Warped Correlation , 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).
[14] Filippo Menczer,et al. The rise of social bots , 2014, Commun. ACM.
[15] Steven Skiena,et al. Polyglot: Distributed Word Representations for Multilingual NLP , 2013, CoNLL.
[16] Greg Ver Steeg,et al. Anchored Correlation Explanation: Topic Modeling with Minimal Domain Knowledge , 2016, TACL.
[17] Kai Kupferschmidt. Bot-hunters eye mischief in German election. , 2017, Science.
[18] Quoc Khanh Nguyen,et al. Blockchain - A Financial Technology for Future Sustainable Development , 2016, 2016 3rd International Conference on Green Technology and Sustainable Development (GTSD).
[19] Roberto Di Pietro,et al. The Paradigm-Shift of Social Spambots: Evidence, Theories, and Tools for the Arms Race , 2017, WWW.
[20] Fabrizio Lillo,et al. $FAKE: Evidence of Spam and Bot Activity in Stock Microblogs on Twitter , 2018, ICWSM.
[21] Jure Leskovec,et al. Global Diffusion via Cascading Invitations: Structure, Growth, and Homophily , 2015, WWW.
[22] Rossano Schifanella,et al. People Are Strange When You're a Stranger: Impact and Influence of Bots on Social Networks , 2012, ICWSM.
[23] Filippo Menczer,et al. Online Human-Bot Interactions: Detection, Estimation, and Characterization , 2017, ICWSM.
[24] Maria Glenski,et al. Characterizing Speed and Scale of Cryptocurrency Discussion Spread on Reddit , 2019, WWW.
[25] Sherali Zeadally,et al. Online deception in social media , 2014, Commun. ACM.
[26] Albert-László Barabási,et al. Scale-free networks , 2008, Scholarpedia.
[27] Christos Faloutsos,et al. Catching Synchronized Behaviors in Large Networks , 2016, ACM Trans. Knowl. Discov. Data.
[28] Roberto Di Pietro,et al. Social Fingerprinting: Detection of Spambot Groups Through DNA-Inspired Behavioral Modeling , 2017, IEEE Transactions on Dependable and Secure Computing.
[29] Alex 'Sandy' Pentland,et al. An Experimental Study of Cryptocurrency Market Dynamics , 2018, CHI.
[30] Benjamin Livshits,et al. The Anatomy of a Cryptocurrency Pump-and-Dump Scheme , 2018, USENIX Security Symposium.
[31] Nasir Ghani,et al. Bitcoin Concepts, Threats, and Machine-Learning Security Solutions , 2018, IEEE Access.
[32] J. Kamps,et al. To the moon: defining and detecting cryptocurrency pump-and-dumps , 2018, Crime Science.
[33] Emilio Ferrara,et al. Disinformation and Social Bot Operations in the Run Up to the 2017 French Presidential Election , 2017, First Monday.
[34] Günter Müller,et al. Economic Analysis of Cryptocurrency Backed Money Laundering , 2015, ECIS.
[35] Young Bin Kim,et al. Predicting Fluctuations in Cryptocurrency Transactions Based on User Comments and Replies , 2016, PloS one.
[36] Mark Fischetti,et al. Weaving the web - the original design and ultimate destiny of the World Wide Web by its inventor , 1999 .
[37] Maurizio Tesconi,et al. Enriching Digital Libraries with Crowdsensed Data - Twitter Monitor and the SoBigData Ecosystem , 2019, IRCDL.
[38] Massimo Bartoletti,et al. Data Mining for Detecting Bitcoin Ponzi Schemes , 2018, 2018 Crypto Valley Conference on Blockchain Technology (CVCBT).
[39] Jon-Patrick Allem,et al. Could Social Bots Pose a Threat to Public Health? , 2018, American journal of public health.
[41] Usman W. Chohan,et al. The Problems of Cryptocurrency Thefts and Exchange Shutdowns , 2018 .
[42] Stefan Evert,et al. Japan's 2014 General Election: Political Bots, Right-Wing Internet Activism, and Prime Minister Shinzō Abe's Hidden Nationalist Agenda , 2017, Big Data.
[43] Kate Starbird,et al. Disinformation’s spread: bots, trolls and all of us , 2019, Nature.
[44] Zibin Zheng,et al. Detecting Ponzi Schemes on Ethereum: Towards Healthier Blockchain Technology , 2018, WWW.
[45] Duncan J. Watts,et al. Collective dynamics of ‘small-world’ networks , 1998, Nature.
[46] Albert,et al. Emergence of scaling in random networks , 1999, Science.
[47] Emilio Ferrara,et al. Social Bots Distort the 2016 US Presidential Election Online Discussion , 2016, First Monday.
[48] Denise Gorse,et al. Mutual-Excitation of Cryptocurrency Market Returns and Social Media Topics , 2018, ICFET '18.
[49] Fred Morstatter,et al. Identifying and Analyzing Cryptocurrency Manipulations in Social Media , 2019, IEEE Transactions on Computational Social Systems.
[50] Filippo Menczer,et al. Arming the public with artificial intelligence to counter social bots , 2019, Human Behavior and Emerging Technologies.
[51] Jon Crowcroft,et al. Do Bots impact Twitter activity? , 2017, WWW.
[52] Wolfgang Härdle,et al. Dynamic Topic Modelling for Cryptocurrency Community Forums , 2016 .
[53] Fabrizio Lillo,et al. Cashtag Piggybacking , 2018, ACM Trans. Web.
[54] Emilio Ferrara. Disinformation and Social Bot Operations in the Run Up to the 2017 French Presidential Election , 2017 .
[55] Jaegul Choo,et al. When Bitcoin encounters information in an online forum: Using text mining to analyse user opinions and predict value fluctuation , 2017, PloS one.
[56] Rui Zhang,et al. Analysis of Twitter to Identify Topics Related to Eating Disorder Symptoms , 2019, 2019 IEEE International Conference on Healthcare Informatics (ICHI).
[57] Kim-Kwang Raymond Choo. Cryptocurrency and Virtual Currency: Corruption and Money Laundering/Terrorism Financing Risks? , 2015 .
[58] Miltiadis D. Lytras,et al. Social Commerce as a Driver to Enhance Trust and Intention to Use Cryptocurrencies for Electronic Payments , 2018, IEEE Access.
[59] Tao Li,et al. Cryptocurrency Pump-and-Dump Schemes , 2019 .
[60] Filippo Menczer,et al. BotOrNot: A System to Evaluate Social Bots , 2016, WWW.
[61] David A. Broniatowski,et al. Weaponized Health Communication: Twitter Bots and Russian Trolls Amplify the Vaccine Debate , 2018, American journal of public health.
[62] Tyler Moore,et al. Analyzing the Bitcoin Ponzi Scheme Ecosystem , 2018, Financial Cryptography Workshops.