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Despite the extensive literature investigating stylometry analysis in authorship attribution research, translator stylometry is an understudied research area. The identification of translator stylometry contributes to many fields including education, intellectual property rights and forensic linguistics. In a two stage process, this paper first evaluates the use of existing lexical measures for the translator stylometry problem. Similar to previous research we found that using vocabulary richness in its traditional form as it has been used in the literature could not identify translator stylometry. This encouraged us to design an approach with the aim of identifying the distinctive patterns of a translator by employing network-motifs. Networks motifs are small sub-graphs which aim at capturing the local structure of a complex network. The proposed approach achieved an average accuracy of 83% in three-way classification. These results demonstrate that classic tools based on lexical features can be used for identifying translator stylometry if they get augmented with appropriate non-parametric scaling. Moreover, the use of complex network analysis and network motifs mining provided made it possible to design features that can solve translator stylometry analysis problems., Competing Interests: The authors have declared that no competing interests exist.

It is not fully understood how cooperation emerges in a population of individuals with no connections or prior experience with each other. Strategy selection that is purely based on accumulated payoffs promotes free riders who put their self interests above that of any group. How could cooperation persist in these settings? Researchers have posited direct or indirect reciprocity as possible explanations but these theories fail if interactions are not repeated or reputations are ignored. Altruistic punishment may provide an answer. Punishers impose a penalty, such as a fine, on defectors. The idea is a sufficiently high enough penalty-or even the threat of a high penalty-will convince defectors that cooperation is more beneficial. The punishment is altruistic because punishers pay a cost to impose a penalty and expect nothing in return (including no future reciprocity). Empirical and human studies have shown when some individuals are punishers, and they are common, cooperation levels tend to increase. But it has never been specified exactly how large this majority of punishers must be to promote cooperation. Here we analyze cooperation, defection and punishment in a social dilemma, public goods game, and precisely identify the necessary conditions to make altruistic punishment an effective strategy for improving group cooperation levels., (Copyright © 2018 Elsevier B.V. All rights reserved.)