January 27, 2022

Conference Paper: “A Crowd-Powered Socially Embedded Search Engine”

Here’s an interesting conference paper by members of the Microsoft Research team.

It will be presented next month at the 7th International AAAI Conference on Weblogs and Social Media.


A Crowd-Powered Socially Embedded Search Engine


Jin-Woo Jeong
Meredith Ringel Morris
Jaime Teevan
Daniel Liebling

Affiliation For All Authors: Microsoft Research


ICWSM 13 Proceedings (via MSR)


People have always asked questions of their friends, but now, with social media, they can broadcast their questions to their entire social network. In this paper we study the re-plies received via Twitter question asking, and use what we learn to create a system that augments naturally occurring “friendsourced” answers with crowdsourced answers. By analyzing of thousands of public Twitter questions and an-swers, we build a picture of which questions receive an-swers and the content of their answers. Because many ques-tions seek subjective responses but go unanswered, we use crowdsourcing to augment the Twitter question asking ex-perience. We deploy a system that uses the crowd to identi-fy question tweets, create candidate replies, and vote on the best reply from among different crowd- and friend-generated answers. We find that crowdsourced answers are similar in nature and quality to friendsourced answers, and that almost a third of all question askers provided unsolicit-ed positive feedback upon receiving answers from this novel information agent.

Direct to Full Text Paper (10 pages; PDF)

About Gary Price

Gary Price (gprice@mediasourceinc.com) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. Before launching INFOdocket, Price and Shirl Kennedy were the founders and senior editors at ResourceShelf and DocuTicker for 10 years. From 2006-2009 he was Director of Online Information Services at Ask.com, and is currently a contributing editor at Search Engine Land.