Disinformation and Social Bot Operations in the Run Up to the 2017 French Presidential Election
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Abstract (arXiv)
Recent accounts from researchers, journalists, as well as federal investigators, reached a unanimous conclusion: social media are systematically exploited to manipulate and alter public opinion. Some disinformation campaigns have been coordinated by means of bots, social media accounts controlled by computer scripts that try to disguise themselves as legitimate human users. In this study, we describe one such operation occurred in the run up to the 2017 French presidential election. We collected a massive Twitter dataset of nearly 17 million posts occurred between April 27 and May 7, 2017 (Election Day). We then set to study the MacronLeaks disinformation campaign: By leveraging a mix of machine learning and cognitive behavioral modeling techniques, we separated humans from bots, and then studied the activities of the two groups taken independently, as well as their interplay. We provide a characterization of both the bots and the users who engaged with them and oppose it to those users who didn't. Prior interests of disinformation adopters pinpoint to the reasons of the scarce success of this campaign: the users who engaged with MacronLeaks are mostly foreigners with a preexisting interest in alt-right topics and alternative news media, rather than French users with diverse political views. Concluding, anomalous account usage patterns suggest the possible existence of a black-market for reusable political disinformation bots.
Key facts. Cited by 26 papers in the map (data through 14 Oct 2026). First posted on arXiv 1 Jul 2017.
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Citing papers per year: 2021: 2; 2022: 6; 2023: 5; 2024: 5; 2025: 7; 2026: 1.
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- 2023Simplistic Collection and Labeling Practices Limit the Utility of Benchmark Datasets for Twitter Bot Detection17 Jan 2023
- 2022Datavoidant: An AI System for Addressing Political Data Voids on Social Media24 Oct 2022
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- 2022MEWS: Real-time Social Media Manipulation Detection and Analysis11 May 2022
- 2022Political Communities on Twitter: Case Study of the 2022 French Presidential Election15 Apr 2022
- 2022Towards a New Science of Disinformation17 Mar 2022
- 2021Identification of Twitter Bots Based on an Explainable Machine Learning Framework: The US 2020 Elections Case Study8 Dec 2021
- 2021Seeing and Believing: Evaluating the Trustworthiness of Twitter Users16 Jul 2021
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- 2023False Information, Bots and Malicious Campaigns: Demystifying Elements of Social Media Manipulationscited by 3
- 2023FREDSum: A Dialogue Summarization Corpus for French Political Debatescited by 3
12 most cited of 25 All 25 (JSON)
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- 2025On the efficacy of old features for the detection of new bots24 Jun 2025
- 2025Boosting Bot Detection via Heterophily-Aware Representation Learning and Prototype-Guided Cluster Discovery1 Jun 2025
- 2025UKElectionNarratives: A Dataset of Misleading Narratives Surrounding Recent UK General Elections8 May 2025
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- 2024Large Language Models Reveal Information Operation Goals, Tactics, and Narrative Frames6 May 2024
- 2024Clustering Document Parts: Detecting and Characterizing Influence Campaigns from Documents27 Feb 2024
12 newest of 25 All 25 (JSON)