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Linguistic relations in oral conversations present how opinions areconstructed and developed in a restricted time. The relations bond ideas,arguments, thoughts, and feelings, re-shape them during a speech, and finallybuild knowledge out of all information provided in the conversation. Speakersshare a common interest to discuss. It is expected that each speaker's replyincludes duplicated forms of words from previous speakers. However, linguisticadaptation is observed and evolves in a more complex path than justtransferring slightly modified versions of common concepts. A conversationaiming a benefit at the end shows an emergent cooperation inducing theadaptation. Not only cooperation, but also competition drives the adaptation oran opposite scenario and one can capture the dynamic process by tracking howthe concepts are linguistically linked. To uncover salient complex dynamicevents in verbal communications, we attempt to discover self-organizedlinguistic relations hidden in a conversation with explicitly stated winnersand losers. We examine open access data of the United States Supreme Court. Ourunderstanding is crucial in big data research to guide how transition states inopinion mining and decision-making should be modeled and how this requiredknowledge to guide the model should be pinpointed, by filtering large amount ofdata.

Tracing Linguistic Relations in Winning and Losing Sides of Explicit Opposing Groups