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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Backchannel (linguistics) | 2/2 | https://en.wikipedia.org/wiki/Backchannel_(linguistics) | reference | science, encyclopedia | 2026-05-05T15:40:37.938749+00:00 | kb-cron |
== Recent research == Research in 2000 has pushed back on the notion of backchannels, in which the listener's role is merely to receive information provided by the speaker. Bavelas, Coates, and Johnson put forth evidence that listeners' responses help shape the content of the speaker's utterances. They grouped acknowledgment tokens into two categories: generic and specific. Generic responses could be considered backchannels and would include mm hm and yeah, while specific responses would involve a reaction to the given content. Examples might include Oh! or a facial display of concern. They transcribed students telling a fellow participant about a close call experience that they had had. With one group of participants, they had the listener perform another task to distract them from the story being told. The researchers asked independent reviewers to code the verbal and visual responses of the narration events as generic or specific. They also asked other independent reviewers to gauge the quality of the narration in each case. They concluded that the responses from the distracted listeners included significantly fewer specific responses than from the undistracted listeners. In addition, they found that the quality of the narration was dramatically lower when the listener was distracted. Their basic contention was that listeners are co-narrators and help the storyteller in his or her narration. In other words, a storyteller tells a better story with an audience that is engaged than one that is not. Tolins and Foxtree have also published research demonstrating how backchannel communication influences speakers. Their research was specifically looking at how speakers respond to generic responses compared to specific responses. In 2017, Kyoto University's Graduate program of Informatics began developing a robot to assist individuals, more specifically the elderly, with mental health through the use of attentive listening. They utilized backchannel generation as a method for the robot to have some form of feedback to feel like a real conversation. Further research is being conducted to be more practical. In 1997 there was a study on 205,000 telephone utterances that showed 19% of those constituted a "backchannel". This study was a part of a new method of "discourse detection" and "statistical modeling" that allowed them to have such a large sample size, giving the possibility of generalizing this data to larger communities.
== See also == Aizuchi Phatic expression
== References ==
== External links == Backchannel Facts by Nigel Ward