Connecting IM Pattern and Selective Perceived Responsiveness to Relationship: A Cluster-Based Approach

dc.citation.epage1074en_US
dc.citation.spage1070en_US
dc.citation.woscount0en_US
dc.contributor.authorLee, Hao-Pingen_US
dc.contributor.authorChen, Kuan-Yinen_US
dc.contributor.authorLin, Chih-Hengen_US
dc.contributor.authorChang, Yung-Juen_US
dc.contributor.department交大名義發表zh_TW
dc.contributor.departmentNational Chiao Tung Universityen_US
dc.date.accessioned2020-10-05T02:01:31Z
dc.date.available2020-10-05T02:01:31Z
dc.date.issued2019-01-01en_US
dc.description.abstractAs people utilize instant messaging (IM) to communicate with people of various relationships, they pay different amounts of attention to and have different communication practices with them of different relationships. However, we haven't seen a close investigation of how users' IM communication patterns relate to different groups of IM contacts. We collected IM logs of 547 sender-recipient pairs from 33 smartphone users over the course of 4 weeks, and used k-mean clustering to identify 6 clusters of these users' IM communication patterns. We illustrate the characteristics of the IM patterns of these distinct clusters as well as how the patterns relate to the relationship between the senders and the recipients within these clusters respectively.en_US
dc.identifier.doi10.1145/3341162.3344841en_US
dc.identifier.isbn978-1-45-036869-8en_US
dc.identifier.journalADJUNCT PROCEEDINGS OF THE 2019 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING AND PROCEEDINGS OF THE 2019 ACM INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS (UBICOMP/ISWC'19 ADJUNCT)en_US
dc.identifier.urihttp://dx.doi.org/10.1145/3341162.3344841en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/155295
dc.identifier.wosnumberWOS:000558324800224en_US
dc.language.isoen_USen_US
dc.subjectresponsivenessen_US
dc.subjectinstant messagingen_US
dc.subjectk-means algorithmen_US
dc.subjectclusteringen_US
dc.titleConnecting IM Pattern and Selective Perceived Responsiveness to Relationship: A Cluster-Based Approachen_US
dc.typeProceedings Paperen_US

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