Responsiveness in instant messaging: predictive models supporting inter-personal communication Export

@inproceedings{citeulike:617160, abstract = {For the majority of us, inter-personal communication is an essential part of our daily lives. Instant Messaging, or IM, has been growing in popularity for personal and work-related communication. The low cost of sending a message, combined with the limited awareness provided by current IM systems result in messages often arriving at inconvenient or disruptive times. In a step towards solving this problem, we created statistical models that successfully predict responsiveness to incoming instant messages -- simply put: whether the receiver is likely to respond to a message within a certain time period. These models were constructed using a large corpus of real IM interaction collected from 16 participants, including over 90,000 messages. The models we present can predict, with accuracy as high as 90.1\%, whether a message sent to begin a new session of communication would get a response within 30 seconds, 1, 2, 5, and 10 minutes. This type of prediction can be used, for example, to drive online-status indicators, or in services aimed at finding potential communicators.}, address = {New York, NY, USA}, author = {Avrahami, Daniel and Hudson, Scott E.}, booktitle = {CHI '06: Proceedings of the SIGCHI conference on Human Factors in computing systems}, citeulike-article-id = {617160}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1124881}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1124772.1124881}, doi = {10.1145/1124772.1124881}, isbn = {1-59593-372-7}, keywords = {availability, awareness, interruptibility, responsiveness}, location = {Montr\'{e}al, Qu\'{e}bec, Canada}, pages = {731--740}, posted-at = {2006-05-08 13:49:08}, priority = {3}, publisher = {ACM}, title = {Responsiveness in instant messaging: predictive models supporting inter-personal communication}, url = {http://dx.doi.org/10.1145/1124772.1124881}, year = {2006} }

TY - CONF ID - citeulike:617160 L3 - citeulike-article-id:617160 N2 - For the majority of us, inter-personal communication is an essential part of our daily lives. Instant Messaging, or IM, has been growing in popularity for personal and work-related communication. The low cost of sending a message, combined with the limited awareness provided by current IM systems result in messages often arriving at inconvenient or disruptive times. In a step towards solving this problem, we created statistical models that successfully predict responsiveness to incoming instant messages -- simply put: whether the receiver is likely to respond to a message within a certain time period. These models were constructed using a large corpus of real IM interaction collected from 16 participants, including over 90,000 messages. The models we present can predict, with accuracy as high as 90.1%, whether a message sent to begin a new session of communication would get a response within 30 seconds, 1, 2, 5, and 10 minutes. This type of prediction can be used, for example, to drive online-status indicators, or in services aimed at finding potential communicators. CY - Montr\'{e}al, Qu\'{e}bec, Canada SN - 1-59593-372-7 AD - New York, NY, USA EP - 740 TI - Responsiveness in instant messaging: predictive models supporting inter-personal communication PB - ACM T2 - CHI '06: Proceedings of the SIGCHI conference on Human Factors in computing systems SP - 731 KW - availability KW - awareness KW - interruptibility KW - responsiveness AU - Avrahami, Daniel AU - Hudson, Scott PY - 2006/// UR - http://dx.doi.org/10.1145/1124772.1124881 ER -