Comparative evaluation of community-aware centrality measures

Rajeh, Stephany; Savonnet, Marinette; Leclercq, Éric; Cherifi, Hocine

doi:10.1007/s11135-022-01416-7

Cited by 31 publications

(12 citation statements)

References 39 publications

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“…While information on age and household size is easy to obtain within a population, the number of contacts and the disease state of contacts is less observable. Community-aware centrality measures have also been studied as a way to prioritize immunization to reduce the size of disease outbreaks [ 29 – 31 ]. While centrality is also hard to observe in communities, the framework presented here could be extended to study the impact of vaccine prioritization based on centrality.…”

Section: Methodsmentioning

confidence: 99%

Prioritizing vaccination based on analysis of community networks

et al. 2022

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Many countries that had early access to COVID-19 vaccines implemented vaccination strategies that prioritized health care workers and the elderly. As barriers to access eased, vaccine prioritization strategies have been relaxed. However, these strategies are still an important tool for decision makers to manage new variants, plan for future booster shots, or stage mass vaccinations. This paper explores the impact of vaccine prioritization strategies using networks that represent communities with different demographics and connectivity. The impact of vaccination is compared to non-medical intervention to reduce transmission. Several sources of uncertainty are considered, including vaccine willingness and mask effectiveness. This paper finds that while prioritization strategies can have a large impact on reducing deaths and peak hospitalization, selecting the best strategy depends on community characteristics and the desired objective. Additionally, in some cases random vaccination performs as well as more targeted prioritization strategies. Understanding these trade-offs is important when planning vaccine distribution.

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Section: Methodsmentioning

confidence: 99%

Prioritizing vaccination based on analysis of community networks

et al. 2022

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“…При этом классические меры центральности учитывают различные локальные или глобальные свойства вершины, но не учитывают структуру сообществ графа. Между тем, для целей сетевого анализа часто важно учитывать именно структуру сообществ, поэтому в последнее время внимание исследователей обращено на основанные на сообществах меры центральности (community-aware centrality measures) [41]. Это означает, что центральности вершин считаются после выделения сообществ и учитывают отдельно инцидентные этой вершине ребра внутри сообщества и между сообществами.…”

Section: задачи анализа графов социальных сетейunclassified

Implicit Communities Defined on the Graph for Interacting Objects

Чеповский¹

2023

Успехи Кибернетики / Russian Journal of Cybernetics

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в работе рассматриваются текущие и перспективные задачи анализа графов, представляющих сложные сети взаимодействующих объектов. Описаны предметные области, для которых актуальны данные модели, рассматриваются практика, проблемы анализа графов социальных сетей и выделения на них неявных сообществ. Обсуждаются основные алгоритмы выделения сообществ на графах и проблема тестирования качества получаемых разбиений. Автором предложены перспективные, на его взгляд, направления развития данной тематики для графов, полученных при импорте данных из реальных социальных сетей. Показана актуальность подходов, предложенных в предыдущих работах автора. the paper considers the problems of analyzing graphs that represent complex networks of interacting objects. The relevant domains are described, social network graph analysis and implicit community detection are considered. The key graph-based community detection algorithms and the quality assessment of their results are discussed. The author proposed promising development trends using the graphs representing actual social networks. The relevance of the approaches proposed in the author’s previous works is also highlighted.

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“…For each of those clusters, we ranked the hashtags according to their descriptiveness (i.e., centrality in the cluster); the centrality measure had to not only distinguish each cluster's hashtags clearly from other clusters' hashtags but also be quickly computable on a large network. Whereas common centrality measures such as degree centrality and betweenness centrality fail to identify the hashtags specific to a single cluster, for they do not weight inside edges against outside ones, communityaware centrality measures incorporate community structure but nevertheless also define the centrality of nodes in the entire network, not in each cluster (Rajeh, Savonnet, Leclercq, & Cherifi, 2022). Thus, we defined an original centrality measure for each hashtag within its local cluster.…”

Section: Hashtag Co-occurrence Networkmentioning

confidence: 99%

Identifying Themes of Right-Wing Extremism in Hindutva Discourse on Twitter

Ghasiya¹,

Ahnert²,

Sasahara³

2022

Preprint

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Hindutva, the core political ideology of India's current ruling party, the Bharatiya Janata Party (BJP), seeks to transform constitutionally secular India into a Hindu Rashtra (`Hindu nation'). Although Hindutva has all of the features of right-wing extremism (RWE), it is nevertheless viewed as a sociopolitical phenomenon due to the Eurocentric nature of RWE discourse. Recent theoretical and analytical research has sought to showcase the similarity between RWE and Hindutva, whereas empirical research on their relationship has not been conducted. To fill that gap, in our study we collected 15 million tweets, and in network analysis, identified prominent themes of RWE, including exclusionary nationalism, conspiracy theories, and anti-minority violence and hate speech among the supporters of Hindutva and BJP. Furthermore, our toxicity analysis performed to understand which themes produced higher levels of toxicity, we found that Hindi-language tweets related to conspiracy theories and anti-minority violence or hate speech were more toxic than English-language tweets. Given that the growing global presence and normalisation of RWE-based ideas and movements are sources of concern for political science researchers, our research broadens the discussion on RWE in the Indian context and invites researchers to further investigate Hindutva from the perspective of RWE.

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Comparative evaluation of community-aware centrality measures

Cited by 31 publications

References 39 publications

Prioritizing vaccination based on analysis of community networks

Prioritizing vaccination based on analysis of community networks

Implicit Communities Defined on the Graph for Interacting Objects

Identifying Themes of Right-Wing Extremism in Hindutva Discourse on Twitter

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