Influence and correlation in social networks

By Aris Anagnostopoulos, Ravi Kumar, Mohammad Mahdian. Knowledge Discovery and Data Mining, 2008

772 citations recorded by the source corpus.

Subfields: Communication, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/471e9d18671d713528bf2255eba68476d5acdf2f

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In Communication

In Statistical and Nonlinear Physics

Citations in the corpus

Portrait of an Online Shopper: Understanding and Predicting Consumer Behavior (2015, background): “Distinct social mechanisms give rise to this correlation [5].”
Homophily and Contagion Are Generically Confounded in Observational Social Network Studies (2010, background): “This idea has considerable plausibility and has been picked up by a number of other authors (Anagnostopoulos et al., 2008; Bramoullé et al., 2009), who have shown that it works as a test for direct influence in some models.”
Social influence analysis in large-scale networks (2009, methodology): “For social influence analysis, [2] and [21] propose methods to qualitatively measure the existence of influence.”
Social contagion theory: examining dynamic social networks and human behavior (2011, background): “computer scientists [87], econometricians [88], statisticians [77], and others [78].”
The tube over time: characterizing popularity growth of youtube videos (2011, background): “A number of studies have analyzed the dynamics of wordof-mouth-like information propagation through friends in social networks [4, 7, 13].”
Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks (2009, methodology): “(25) argue ‘‘if influence does not play a role, even though an agent’s probability of activation could depend on her friends, the timing of such activation should be independent of the timing of other agents.”
The Simple Rules of Social Contagion (2013, background): “This biological metaphor serves as a starting point for many analyses of information spread [1, 15, 22, 24].”
The role of social networks in information diffusion (2012, background): “Observational studies of online contagion [4, 9, 15, 30] not only find evidence of temporal clustering, but also observe a similar relationship between the likelihood of contagion and the number of infected contacts.”
Information diffusion in online social networks: a survey (2013, background): “This e↵ect is known as social influence [2], and is defined as follows:”
Social Networks and Causal Inference (2013, background): “This argument, which can be traced back to Duncan et al. (1968) and was formulated in Anagnostopoulos et al. (2008) as the edge-reversal test, may not hold in situations where there is peer selection, sampling errors, or spatial dependence in the network data, points we return to below.”
Scalable Influence Maximization in Social Networks under the Linear Threshold Model (2010, background): “Several studies design machine learning algorithms to extract influence cascade model parameters from real datasets [11], [12], [13], [14], which can be used to generate influence graphs studied in this paper.”
Open challenges for data stream mining research (2014, background): “Depending on the complexity of the queries supported, it might be difficult to express graph algorithms intuitively in MapReduce graph models, consequently databases such as Titan [4], DEX [3], and Neo4j [2] should be compared for graph implementations.”
A Neural Influence Diffusion Model for Social Recommendation (2019, background): “information diffuses in the social networks, users are influenced by their social connections with the social influence theory, leading to the phenomenon of similar preferences among social neighbors [3, 4, 14, 29]. Social regularization has been empirically proven effective for social recommendatio”
Microscopic Social Influence (2012, background): “It is well recognized that social inﬂuence is one complex and subtle force that governs these dynamics [4, 5]: the actions of one individual may induce his/her friends to behave in a similar way via their social connections.”