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Deriving a zero-truncated modelling methodology to analyse capture–recapture data from self-reported social networks
Capture–recapture (CRC) is widely used to estimate the size ( N ) of hidden human populations (e.g., the homeless) from the overlap of sample units...
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Detecting Changes in Dynamic Social Networks Using Multiply-Labeled Movement Data
The social structure of an animal population can often influence movement and inform researchers on a species’ behavioral tendencies. Animal social...
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Learning social networks from text data using covariate information
Accurately describing the lives of historical figures can be challenging, but unraveling their social structures perhaps is even more so. Historical...
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Prediction of brand stories spreading on social networks
Online social network is a major media for many types of information communication. Although the primary purpose of social networks is to connect...
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An analytic strategy for data processing of multimode networks
Complex network data structures are considered to capture the richness of social phenomena and real-life data settings. Multipartite networks are an...
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Random networks with heterogeneous reciprocity
Users of social networks display diversified behavior and online habits. For instance, a user’s tendency to reply to a post can depend on the user...
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Poisson Edge Growth and Preferential Attachment Networks
When modeling a directed social network, one choice is to use the traditional preferential attachment model, which generates power-law tail...
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Mining networks in MARKUS: A study of Chosŏn interpreters’ trade networks in Qing China
This article presents a study on the trade networks reported in Korean envoys’ travelogues Yŏnhaengnok (燕行錄, Chosŏn envoys’ travelogues) using the...
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Social Media Analytics
Social media platforms are powerful for businesses to gain insight into how their customers feel about their company, product, or service. This...
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A comprehensive framework for link prediction in multiplex networks
The idea of predicting links in multiplex networks has gained increasing interest in recent years. In this paper, we propose a comprehensive...
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Mining and Modelling Complex Networks
Mining complex networks represented as graphs is now a well-established sub-field within data science. Analyzing social networks by investigating...
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Statistically validated coeherence and intensity in temporal networks of information flows
We propose a method for characterizing the local structure of weighted multivariate time series networks. We draw intensity and coherence of network...
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Search Regret and Social Networks
I present a model with social networks and search regret disutility. The focus is on the number of the Burdett–Judd-type equilibria. In this model,...
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Generative Methods for Social Media Analysis
This book provides a broad overview of the state of the art of the research in generative methods for the analysis of social media data. It...
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Supervised Classification for Link Prediction in Facebook Ego Networks With Anonymized Profile Information
Social networks are very dynamic objects where nodes and links are continuously added or removed. Hence, an important but challenging task is link...
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On reading and interpreting black box deep neural networks
The deep neural networks used in computer vision and in recent large language models are widely recognized as black boxes, a term that describes...
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Web and Social Media Analytics Strategy
An analytics strategy helps an organization make better decisions using data and analytics. While web analytics helps organizations identify how to...
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The Foundations of Social Media Analytics
Social media analytics is the process of deriving meaning from social media data to make better business decisions. Social media platforms offer...
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Networks as mediating variables: a Bayesian latent space approach
The use of network analysis to investigate social structures has recently seen a rise due to the high availability of data and the numerous insights...
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Special issue on statistical analysis of networks
The special issue on Statistical Analysis of Networks aspires to convey the breadth and depth of statistical learning with networks, ranging from...