Stepwise segmented regression analysis: An iterative statistical algorithm to detect and quantify evolutionary and revolutionary transformations in longitudinal data

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Abstract

This text offers a number of new, innovative measures for use in studying human behavior and social systems, particularly in social media and organizationalcontexts. Briefly, Ignajatovic, Rezvani, and Bertino 2015 discussed assessments of content reliability and contributor trustworthiness, as did Mustaro, Frango, Gobbato, and Kuma 2015. Russell, Still, and Huhtama ki 2015 offered a framework for measuring ecosystemic relational capital. Matei 2015 detailed the Visible Effort tool for measuring system-wide social entropy. And Wei, Zhu, Liu, Matei, and Britt 2015 used activity data to profile Wikipedia users and classify them based upontheir elite stature or lack thereof. These metrics serve to build upon more rudimentary figures like the sheer number of followers of a given user or the amount of content contributed in terms of post count or word count, and they join the array of increasingly sophisticated tools developed over the years that we may use to evaluate social processes and products in the offline and online realms alike.

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Britt, B. C. (2015). Stepwise segmented regression analysis: An iterative statistical algorithm to detect and quantify evolutionary and revolutionary transformations in longitudinal data. In Transparency in Social Media: Tools, Methods and Algorithms for Mediating Online Interactions (pp. 125–144). Springer International Publishing. https://doi.org/10.1007/978-3-319-18552-1_7

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