Detecting Potential Cyber Armies of Election Campaigns Based on Behavioral Analysis

Wang, Ming-Hung; Nguyen, Nhut-Lam; Dow, Chyi‐Ren

doi:10.1007/978-3-030-05414-4_35

Cited by 4 publications

(4 citation statements)

References 11 publications

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“…eu). In addition, there are algorithms for identifying artificial accounts (Wang et al 2019;Schuchard et al 2019;Yang et al 2020) and automatically classifying misinformation or propaganda (Guarino et al 2020).…”

Section: Disinformation Campaignsmentioning

confidence: 99%

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Maximum entropy networks for large scale social network node analysis

2022

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Recently proposed computational techniques allow the application of various maximum entropy network models at a larger scale. We focus on disinformation campaigns and apply different maximum entropy network models on the collection of datasets from the Twitter information operations report. For each dataset, we obtain additional Twitter data required to build an interaction network. We consider different interaction networks which we compare to an appropriate null model. The null model is used to identify statistically significant interactions. We validate our method and evaluate to what extent it is suited to identify communities of members of a disinformation campaign in a non-supervised way. We find that this method is suitable for larger social networks and allows to identify statistically significant interactions between users. Extracting the statistically significant interaction leads to the prevalence of users involved in a disinformation campaign being higher. We found that the use of different network models can provide different perceptions of the data and can lead to the identification of different meaningful patterns. We also test the robustness of the methods to illustrate the impact of missing data. Here we observe that sampling the correct data is of great importance to reconstruct an entire disinformation operation.

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Section: Disinformation Campaignsmentioning

confidence: 99%

“…In addition, there are algorithms for identifying artificial accounts (Wang et al. 2019 ; Schuchard et al. 2019 ; Yang et al.…”

Section: Introductionmentioning

confidence: 99%

Maximum entropy networks for large scale social network node analysis

2022

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“…This is demonstrated by a data analysis conducted by one of our students, which reveals how certain accounts on a well-known bulletin board (Ptt) in Taiwan promoted former presidential candidate Han Kuo-yu during local mayoral elections in November 2018 (Qiu, 2019). Prior research has produced strong evidence for astroturfing activities connected to Mayor Ko Wen-Je during Taipei’s 2014 (Ko & Chen, 2015) and 2018 (M.-H. Wang et al, 2019) mayoral elections. These findings were later confirmed by an investigative report that included interviews with people involved in online astroturfing activities (H.…”

Section: Seeing Taiwan Through the Lens Of Hybriditymentioning

confidence: 99%

Untangling Taiwan’s Hybridity With Structural Dysfunctions

Rauchfleisch

Chi

2020

Social Media + Society

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Taiwan’s exceptionally high Internet penetration and social media adoption rates, combined with the growing centrality of digital tools and networks in shaping national politics, make it an interesting case for Internet researchers. This essay considers Andrew Chadwick’s notion of The Hybrid Media System in the context of recent political events in Taiwan. While Chadwick’s analysis is particularly useful in understanding political anomalies like the Sunflower Movement, we argue for the value of considering more substantial long-standing structural issues in attempts to understanding the political media landscape in Taiwan. Using the examples of online astroturfing during political campaigns and the spread of disinformation during the Kansai airport incident, we point out that long-standing structural factors such as the dysfunctional practices of journalists in newsrooms, the clear political slants of media in accordance with media ownership, and the traditional political power rooted in the society hold enduring sway on how politics is mediated.

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“…Hoaxy [35] for the tracking of social news sharing, and various fact checking websites such as FactCheck[2], PolitiFact [3] or EUvsDisinfo [4]. In addition, there are algorithms for identifying artificial accounts [34,40,42] and automatically classifying misinformation or propaganda [19].…”

Section: Introductionmentioning

confidence: 99%

Maximum Entropy Networks Applied on Twitter Disinformation Datasets

Clerck

Utterbeeck

Petit

et al. 2022

Studies in Computational Intelligence

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Identifying and detecting disinformation is a major challenge. Twitter provides datasets of disinformation campaigns through their information operations report. We compare the results of community detection using a classical network representation with a maximum entropy network model. We conclude that the latter method is useful to identify the most significant interactions in the disinformation network over multiple datasets. We also apply the method to a disinformation dataset related to COVID-19, which allows us to assess the repeatability of studies on disinformation datasets.

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Detecting Potential Cyber Armies of Election Campaigns Based on Behavioral Analysis

Cited by 4 publications

References 11 publications

Maximum entropy networks for large scale social network node analysis

Maximum entropy networks for large scale social network node analysis

Untangling Taiwan’s Hybridity With Structural Dysfunctions

Maximum Entropy Networks Applied on Twitter Disinformation Datasets

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