CSCW Session – Oh Behave: Politeness and Emotion in CSCW

11Nov08

Linguistic Mimicry and Trust in Text-Based CMC

Lauren Scissors et al, Northwestern University

In face to face settings, people establish rapport through behavior mimicry, to get people to like them.

Lack this in text. Is there linguistic mimicry?

Previous research indicates that f-to-f speech patterns, people tend to adopt partner’s speach patterns.

Also, research on trust in CMC environments. Takes longer to develop trust in CMC.

Hypthoesis: Text-chat enviormenent: high levels of linguistic mimicry associated with higher level of trust, lower mimicry associated with lower level of trust. Hmmm, I’m skeptical.

Description of method…..examined mimicry: using lexical mimicry (noun or noun phrase), Text-chat abbreviation mimicry (like “u didn’t do it”), and syntactic, emotion-related character (emoticons).

Hmm, deeply skeptical of abbreviation mimicry.

WIthin-session mimicry led to higher trust. Across-session mimicry lower trust. Hm, not sure i buy it. Many approach the microphone for some of the ol’ rip-n-tear action.

Mind your Ps and Qs: The Impact of politeness and rudeness in online communities

Moira Burke and Bob Kraut, CMU

Goals

  • determine impact of polite or rude language in online commnity interaction (newcomer integration, more efficient groupwork, death by monster (?))
  • Build machine learning tools to automatically detect polite language
  • Extend linguistic politeness theory to social interactions between strangers online

Method: survey to rate politeness of messages  in a discussion group. Code message for presence or active of specific strategies around politeness.

Linguistic politeness theory, Brown and Levinson: 15 positive strategies to increase person’s positive social value, and 10 negative strategies to decrease. Interesting, should read that sometime.

Generally, they found that rude behavior in a politics group  “helps” (that is, gets replies), where as in technical groups tend to not get responses. Well, okay. Keep in mind, that previous research points out that getting responses is what fuels future participation.

Next steps: train machine to detect language. A “Politness checker” like a grammar checker. Hm, not sure i like that. Good writing is the avoidance of cliche, not the repetition of patterns observed elsewhere.

I am waiting – Timing and responsiveness in semi-synchronous communication

Within synchronous communication, lack of responsiveness is immediately problemmatic. But what is the affect in asynchronous?

In IM, users can choose whether and when to respond to EVERY point of the conversation. And, users typically multitask n IM communications.

Objective of study: a deeper understanding of factors that affect responsiveness. They do this with a survey. Hmm. This seems kind of obvious: resposiveness is a runction of how busy i am and the perceived importance of the message. Perceived importance culd be bucketed into a few things (who sent it, subject matter, provocation, etc).

Their list:

  • Identify of the buddy
  • relationship with buddy
  • time since liast message
  • whtehr message window already existed
  • whether message window was in focus

Results HIghlights and Implications

Relationship category did not have a significant impact on responsiveness. Hm, that’s surprising. But there were significant differences between individuals.

Work-fragmentation is a strong indicator of faster responsiveness

  • More keyboard activity
  • More mouse activity
  • More app-window switches.
  • Hmm, that’s interesting too.

Also: Faster responsiveness if the IM window was already open. And, signifiant efrect whether the window is covered or not. Shocker!

  • Longer messages got faster responses
  • Questions got faster responses
  • URLs got slower responsiveness
  • Emoticons marginally slower responses.
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