1,721,059 research outputs found
Individual Performance in Team-based Online Games
No full textLeague of Legends dataset associated with the paper titled:
Individual Performance in Team-based Online Games by Sapienza, A., Zeng, Y., Bessi, A., Lerman, K., Ferrara, E. (Royal Society Open Science 5 180329, 2018)
The dataset adopted for this study was collected using the League of Legends' Riot Games API (Riot Games API: https://developer.riotgames.com/)
It consists of 435,000 matches played by a sample of 1,120 of the most active players, i.e., those who played more than 100 games.
The data contains information about matches, including
match time and duration, and the number of deaths, kills, earned gold, gold spent, etc. for each player in each match
Propaganda and Misinformation on Facebook and Twitter during the Russian Invasion of Ukraine
Full text linkExposing Cross-Platform Coordinated Inauthentic Activity in the Run-Up to the 2024 U.S. Election
No full textUncovering coordinated cross-platform information operations: Threatening the integrity of the 2024 U.S. presidential election
No full textInformation operations (IOs) pose a significant threat to the integrity of democratic processes, with the potential to influence election-related online discourse. In anticipation of the 2024 U.S. presidential election, we present a study aimed at uncovering the digital tracesof coordinated IOs on X (formerly Twitter). Using our machine learning framework for detecting online coordination, we analyze adataset comprising election-related conversations on X from May to July 2024. This reveals a network of coordinated inauthenticactors, displaying notable similarities in their link-sharing behaviors. Our analysis shows concerted efforts by these accounts todisseminate misleading, redundant, and biased information across the Web through a coordinated cross-platform information operation:The links shared by this network frequently direct users to other social media platforms or mock news sites featuring low-qualitypolitical content and, in turn, promoting the same X and YouTube accounts. Members of this network also shared deceptive imagesgenerated by AI, accompanied by language attacking political figures and symbolic imagery intended to convey power and dominance.While X has suspended or restricted a subset of these accounts, 75 percent of the coordinated network remains active, garneringsubstantial traction over time: The suspicious Web sites promoted by this coordinated network are shared thousands of times per day bythe X user base, further amplifying their reach and potential impact. Our findings underscore the critical role of developingcomputational models to scale up the detection of threats on large social media platforms, and emphasize the broader implications ofthese techniques to detect IOs across the wider Web
IOHunter: Graph Foundation Model to Uncover Online Information Operations
No full textSocial media platforms have become vital spaces for public discourse, serving as modern agorás where a wide range of voices influence societal narratives. However, their open nature also makes them vulnerable to exploitation by malicious actors, including state-sponsored entities, who can conduct information operations (IOs) to manipulate public opinion.
The spread of misinformation, false news, and misleading claims threatens democratic processes and societal cohesion, making it crucial to develop methods for the timely detection of inauthentic activity to protect the integrity of online discourse. In this work, we introduce a methodology designed to identify users orchestrating information operations, a.k.a. IO drivers, across various influence campaigns. Our framework, named IOHunter, leverages the combined strengths of Language Models and Graph Neural Networks to improve generalization in supervised, scarcely-supervised, and cross-IO contexts. Our approach achieves state-of-the-art performance across multiple sets of IOs originating from six countries, significantly surpassing existing approaches. This research marks a step toward developing Graph Foundation Models specifically tailored for the task of IO detection on social media platforms
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
- …
