2018
DOI: 10.1145/3274312
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Coloring in the Links

Abstract: The richness that characterizes relationships is often absent when they are modeled using computational methods in network science. Typically, relationships are represented simply as links, perhaps with weights. The lack of finer granularity is due in part to the fact that, aside from linkage and strength, no fundamental or immediately obvious dimensions exist along which to categorize relationships. Here we propose a set of dimensions that capture major components of many relationships -derived both from rele… Show more

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Cited by 19 publications
(9 citation statements)
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“…Previous work pointed towards the necessity of distinguishing edge types in order to adequately understand overlapping community structure of social networks 1 , or the measurement and modeling of weak ties and their importance in network cohesion 43 , 45 . For automatically collected large-scale networks, it is sometimes possible to infer edge types from the communication content 26 or to capture different interactions between nodes by the data collection design 36 , 53 . However, these examples remain exceptions and limited to the particular measurement setting used in these studies, or include only a small number of nodes (see 6 , 51 and 27 , Chapter 3).…”
Section: Introductionmentioning
confidence: 99%
“…Previous work pointed towards the necessity of distinguishing edge types in order to adequately understand overlapping community structure of social networks 1 , or the measurement and modeling of weak ties and their importance in network cohesion 43 , 45 . For automatically collected large-scale networks, it is sometimes possible to infer edge types from the communication content 26 or to capture different interactions between nodes by the data collection design 36 , 53 . However, these examples remain exceptions and limited to the particular measurement setting used in these studies, or include only a small number of nodes (see 6 , 51 and 27 , Chapter 3).…”
Section: Introductionmentioning
confidence: 99%
“…The theory posits that a speaker can enhance their chances of changing the hearer's mind by loading their arguments with the appropriate intent, for example by conveying trust and willingness to share knowledge (Habermas 1979). Prior research has identified universal dimensions of social pragmatics (Deri et al 2018), and developed a transformer-based tool to reliably capture the presence of these dimensions in conversational language (Choi et al 2020). The tool was tested on online debates for which a ground truth of successful arguments was available, showing that the most persuasive arguments are characterized by the dimensions indicated by the theory: factual knowledge, expression of trust, and appeals to the similarity between points of view (Monti et al 2022).…”
Section: Methods Experimental Designmentioning
confidence: 99%
“…Social Dimensions. We then consider as features the social dimensions introduced by [79], a set of universal categories of social pragmatics. Previous research has analyzed the presence of these dimensions in language and conversations, finding them to be highly predictive of opinion change in online debates [70,80,81].…”
Section: Textual Analysismentioning
confidence: 99%