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    Challenges of and approaches to data collection across platforms and time: Conspiracy-related digital traces as examples of political contention
    (2024) Heft, Annett; Bühling, Kilian; Zhang, Xixuan; Schindler, Dominik; Milzner, Miriam
    Taking the example of conspiracy-related communication online as one form of contentious politics, this study examines the data collection challenges for multidimensional comparative research across platforms, time, and cultural embeddings. It compares the architectures and features relevant to data collection, access regimes, and use cultures for a set of digital platforms and communication venues. Differentiating between actor- and content-based strategies, this study discusses the potentials and limitations of these approaches, considering differences in platforms, temporal dynamics, and cultural embeddings as well as several layers of equivalence. The discussion highlights crucial insights into designing data collection strategies in multidimensional comparative studies.
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    Grounding force-directed network layouts with latent space models
    (2023) Gaisbauer, Felix; Pournaki, Armin; Banisch, Sven; Olbrich, Eckehard
    Force-directed layout algorithms are ubiquitously used tools for network visualization. However, existing algorithms either lack clear interpretation, or they are based on techniques of dimensionality reduction which simply seek to preserve network-immanent topological features, such as geodesic distance. We propose an alternative layout algorithm. The forces of the algorithm are derived from latent space models, which assume that the probability of nodes forming a tie depends on their distance in an unobserved latent space. As opposed to previous approaches, this grounds the algorithm in a plausible interaction mechanism. The forces infer positions which maximise the likelihood of the given network under the latent space model. We implement these forces for unweighted, multi-tie, and weighted networks. We then showcase the algorithm by applying it to Facebook friendship, and Twitter follower and retweet networks; we also explore the possibility of visualizing data traditionally not seen as network data, such as survey data. Comparison to existing layout algorithms reveals that node groups are placed in similar configurations, while said algorithms show a stronger intra-cluster separation of nodes, as well as a tendency to separate clusters more strongly in multi-tie networks, such as Twitter retweet networks.
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    Digital Inclusion Through Algorithmic Knowledge: Curated Flows of Civic and Political Information on Instagram
    (2024) Boulianne, Shelley; Hoffmann, Christian P.
    Social media platforms are a critical source of civic and political information. We examine the use of Instagram to acquire news as well as civic and political information using nationally representative survey data gathered in 2019 in the US, the UK, France, and Canada (n = 2,440). We investigate active curation practices (following news organizations, political candidates or parties, and nonprofit organizations or charities) and passive curation practices (liking friends’ political posts and those from parties or politicians and nonprofits or charities). Young adults (18 to 24 years) are far more likely to curate their Instagram feed than older adults in all four countries. We consider two possible explanations for this behavior: political interest and an understanding of how algorithms work. Young adults have more (self-assessed) knowledge of algorithms in all four countries. Algorithmic knowledge relates to curation practices, but there are some cross-national differences. Algorithmic knowledge is theoretically relevant for passive curation practices and the UK sample provides support for the stronger role of algorithmic knowledge in passive than active curation. In all four countries, political interest positively relates to active and passive curation practices. These findings challenge depictions of young adults as news avoiders; instead, they demonstrate that algorithmic knowledge can help curate the flow of information from news organizations as well as civic and political groups on Instagram. While algorithmic knowledge enables youth’s digital inclusion, for older adults, the lack of knowledge may contribute to digital exclusion as they do not know how to curate their information flows.
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    A centrality analysis of the Lightning Network
    (2023) Zabka, Philipp; Förster, Klaus-T.; Decker, Christian; Schmid, Stefan
    Blockchain technology has a huge impact on our digital society by enabling a more decentralized economy and policy making. This decentralization is also pivotal in payment Payment channel networks (PCNs), including the Lightning Network, have emerged as a promising solution to the scalability challenges that many blockchain-based cryptocurrencies, like Bitcoin, grapple with. These PCNs, while innovative, also inherit the rigorous dependability demands of the blockchain. A pivotal aspect of this dependability is the need for a high degree of decentralization, essential for mitigating liquidity bottlenecks and on-path attacks.
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    Cascades or salmons? Longitudinal upstream and downstream effects of political participation
    (2024) Ohme, Jakob; Azrout, Rachid; Moeller, Judith
    Digitally networked and new, unconventional activities allow citizens to participate politically in activities that are low in the effort and risks they bear. At the same time, low-effort types of participation are more loosely connected to democratic political systems, thereby challenging established modes of political decision-making. This can set in motion two competing dynamics: While some citizens move closer to the political system in their activities (upstream effects), others engage in political activities more distant from it (downstream effects). This study investigates non-electoral participation trajectories and tests intra-individual change in political participation types over time, exploring whether such dynamics depend on citizens’ exposure to political information. Utilizing a three-wave panel survey (n = 3490) and random intercept cross-lagged panel models with SEM, we find more evidence for downstream effects but detect overall diverse participation trajectories over time and a potentially crucial role of elections for non-electoral participation trajectories.