With a little help from my friends

A typical person has numerous online friends that, according to studies, the person often consults for opinions and advice. However, public broadcasting a question to all friends risks social capital when repeated too often, is not tolerant to topic sensitivity, and can result in no response, as the...

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Bibliographische Detailangaben
Hauptverfasser: Nandi, A., Paparizos, S., Shafer, J. C., Agrawal, R.
Format: Tagungsbericht
Sprache:eng
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Beschreibung
Zusammenfassung:A typical person has numerous online friends that, according to studies, the person often consults for opinions and advice. However, public broadcasting a question to all friends risks social capital when repeated too often, is not tolerant to topic sensitivity, and can result in no response, as the message is lost in a myriad of status updates. Direct messaging is more personal and avoids these pitfalls, but requires manual selection of friends to contact, which can be time consuming and challenging. A user may have difficulty guessing which of their numerous online friends can provide a high quality and timely response. We demonstrate a working system that addresses these issues by returning an ordered subset of friends predicting (a) near-term availability, (b) willingness to respond and (c) topical knowledge, given a query. The combination of these three aspects are unique to our solution, and all are critical to the problem of obtaining timely and relevant responses. Our system acts as a decision aid - we give insight into why each friend was recommended and let the user decide whom to contact.
ISSN:1063-6382
2375-026X
DOI:10.1109/ICDE.2013.6544926