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E.24 Information Exchange
E.24 Information Exchange
E.24
Word count minus first-person singular pronouns was taken as a measure of information exchange. Then converted to z-scores.
- Word count minus first-person singular pronouns --> "info_exchange_wordcount"
- Compute the z-score at the chat level: compute z-score for each message across all conversations --> "zscore_chats"
- Compute the z-score at the conversation level: group by batch and round, then compute the z-score for each conversation --> "zscore_conversation"
According to E.24, "The degree of information exchange is reflected in group communication in part by the quantity of on-task communication." (p.3) To calculate on-task communication, "Word count is a commonly used crude measure of the total information exchanged. First-person singular pronouns suggest self-focus rather than topic focus, thus we refined the crude measure by penalizing for self-focus rather than topic focus."
Note that in our particular case, our dataset is jury data. Each participant expressed their own opinions in the discussion in order to reach a unanimous decision. Personal opinion acts as an important part in on-task communications, so we might put a question mark on the rationale of penalizing self-focus messages.
Besides, this method does not capture the quality of the information itself because it solely relies on the quantity. A person might say a lot of words but none of the information is meaningful to the topic.
Overall, this is not a very informative computational method to measure the degree of information exchange.
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z-score
Page 4 in E.24
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