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Analysis of institutional authors

Villar-Rodriguez, GuillermoAuthorMartin, AlejandroCorresponding AuthorHuertas-Tato, JavierAuthorCamacho, DavidAuthor

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December 10, 2024
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DisTrack: A New Tool For Semi-automatic Misinformation Tracking in Online Social Networks

Publicated to: Cognitive Computation. 17 (1): 12- - 2025-02-01 17(1), DOI: 10.1007/s12559-024-10378-x

Authors:

Villar-Rodríguez, G; Huertas-García, A; Martín, A; Huertas-Tato, J; Camacho, D
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Affiliations

Univ Politecn Madrid, Dept Sistemas Informat, Madrid, Spain - Author

Abstract

This article introduces DisTrack, a methodology and a tool developed for tracking and analyzing misinformation within online social networks (OSNs). DisTrack is designed to combat the spread of misinformation through a combination of natural language processing (NLP) social network analysis (SNA) and graph visualization. The primary goal is to detect misinformation, track its propagation, identify its sources, and assess the influence of various actors within the network. DisTrack's architecture incorporates a variety of methodologies including keyword search, semantic similarity assessments, and graph generation techniques. These methods collectively facilitate the monitoring of misinformation, the categorization of content based on alignment with known false claims, and the visualization of dissemination cascades through detailed graphs. The tool is tailored to capture and analyze the dynamic nature of misinformation spread in digital environments. The effectiveness of DisTrack is demonstrated through three case studies focused on different themes: discredit/hate speech, anti-vaccine misinformation, and false narratives about the Russia-Ukraine conflict. These studies show DisTrack's capabilities in distinguishing posts that propagate falsehoods from those that counteract them, and tracing the evolution of misinformation from its inception. The research confirms that DisTrack is a valuable tool in the field of misinformation analysis. It effectively distinguishes between different types of misinformation and traces their development over time. By providing a comprehensive approach to understanding and combating misinformation in digital spaces, DisTrack proves to be an essential asset for researchers and practitioners working to mitigate the impact of false information in online social environments.
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Keywords

Covid-19DisinformationEconomic and social effectsHoaxLanguage inferenceLanguage processingMisinformationNatural language inferenceNatural language processing systemsNatural languagesSemantic similaritSemantic similaritySemanticsSemi-automaticsSocial network analysisSpreaTransformerTransformersVisualization

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Cognitive Computation due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2025, it was in position 71/314, thus managing to position itself as a Q1 (Primer Cuartil), in the category Neurosciences.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-25:

  • WoS: 2
  • Scopus: 2
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-25:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 12.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 12 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 4.
  • The number of mentions on the social network X (formerly Twitter): 1 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/88854/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 178
  • Downloads: 112
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Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (VILLAR RODRIGUEZ, GUILLERMO) and Last Author (CAMACHO FERNANDEZ, DAVID).

the author responsible for correspondence tasks has been MARTIN GARCIA, ALEJANDRO.

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Awards linked to the item

This work has been funded by the project PCI2022-134990-2 (MARTINI) of the CHISTERA IV Cofund 2021 program, funded by MCIN/AEI/10.13039/ 501100011033 and by the "European Union NextGenerationEU/PRTR"; by the research project DisTrack: Tracking disinformation in online social networks through deep natural language processing, granted by Mobile World Capital Foundation; by the Spanish Ministry of Science and Innovation under FightDIS(PID2020-117263GB-I00); by MCIN/AEI/10.13039/501100011033/and European Union NextGenerationEU/PRTR for XAI-Disinfodemics (PLEC 2021-007681) grant, by European Comission under IBERIFIERPlus - Iberian Digital Media Observatory (DIGITAL-2023-DEPLOY-04-EDMO-HUBS 101158511); and by EMIF managed by the Calouste Gulbenkian Foundation, in the project MuseAI.
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