A Dataset of Coordinated Cryptocurrency-Related Social Media Campaigns
January 16, 2023 Β· Declared Dead Β· π International Conference on Web and Social Media
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Karolis Zilius, Tasos Spiliotopoulos, Aad van Moorsel
arXiv ID
2301.06601
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CR,
cs.CY,
cs.IR,
cs.SI
Citations
5
Venue
International Conference on Web and Social Media
Last Checked
4 months ago
Abstract
The rise in adoption of cryptoassets has brought many new and inexperienced investors in the cryptocurrency space. These investors can be disproportionally influenced by information they receive online, and particularly from social media. This paper presents a dataset of crypto-related bounty events and the users that participate in them. These events coordinate social media campaigns to create artificial "hype" around a crypto project in order to influence the price of its token. The dataset consists of information about 15.8K cross-media bounty events, 185K participants, 10M forum comments and 82M social media URLs collected from the Bounties(Altcoins) subforum of the BitcoinTalk online forum from May 2014 to December 2022. We describe the data collection and the data processing methods employed and we present a basic characterization of the dataset. Furthermore, we discuss potential research opportunities afforded by the dataset across many disciplines and we highlight potential novel insights into how the cryptocurrency industry operates and how it interacts with its audience.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted