Co-Evolution of Social Networks and Language Use

Speaker: W. Quin Yow

Writer: Sreetej Lakkam

The advent of language has been base for rapid development in human interactions since the age of early man. The importance of language is essential to every aspect of our daily lives. Communication among different entities of the society drives us ahead and helps in personality development.

Professor Yow’s group focuses on understanding the role of language usage in student social networks using advanced data acquisition tools. They intend to understand the effect of linguistics in a multilingual environment, especially in formation of social networks among students from different cultural background.

The research outlines the effect of homophily on social networks and how local language facilitates initial interactions among college students. Further the impact of assimilation in group formation is explained. The homophilic effects due to factors like language proficiency, nationality and code switching capabilities on friendship networks is analysed in great detail. Reported and inferred social networks of freshmen and sophomores student groups are considered and compared on lines of language usage, co-location and call patterns.

The usage of stochastic actor based model aided in an accurate representation of the influence of variety of factors like demographics, linguistic skills, and common interests on the dynamics of friendship networks. Further assuming friendship network evolution is based on student interactions and usage of students as nodes, provided an effective platform to study the effect bilingual and multi-lingual backgrounds on social networking.

On comparing the homophilic effects on different groups it has been inferred that, freshmen students tend to form friendship with individuals of same cohort and similar code switching behaviours. On the contrast sophomores tended to bond with individuals with same language balance but different code-switching behaviours.

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Co-Evolution of Social Networks and Language Use

The method of using nodal network approach for analysing the changes in student interaction can be utilised in other networking areas like swarm dynamics. The clustering coefficient of nodal networks can be used as an indicator of effectiveness of the network. It can provide data to analyse

The time taken for information exchange within the network. The effect of node displacement on the whole network.

In social networks among friends the call patterns and co-location data helps in better understanding interaction between individual students.

The dynamic analysis of mobile positioning and calling patterns to predict friendship and social interaction rate among culturally varied individuals is interesting. The research group’s usage of “social statistics” app for data acquisition in periodic intervals and creation of binary matrices for various factors is a novel approach. This analysis data of interaction patterns of an individual, over a span of couple of years can be used to predict emergent social behavioural patterns in future.

Research orientation in studying social network evolution by using mobile phone data provides a distinctive advantage in this digital age. Several factors like continuous access to mobile networks and mobile usage patterns among young adults of this decade provide abundant opportunities for researchers. This approach can lead to development of better prediction algorithms useful in other domains of research. Further the analysis of social network dynamics may motivate research teams to build tools for improving human interactions.

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