Graduate School and Research Center in Digital Sciences

Spotting trends: The wisdom of the few

Sha, Xiaolan; Quercia, Daniele; Dell'Amico, Matteo; Michiardi, Pietro

RECSYS 2012, ACM Recommender Systems Conference, September 9-13, 2012, Dublin, Ireland

Socialmedia sites have used recommender systems to suggest items users might like but are not already familiar with. These items are typically movies, books, pictures, or songs. Here we consider an alternative class of items - pictures posted by design-conscious individuals. We do so in the context of a mobile application in which users find "cool" items in the real world, take pictures of them, and share those pictures online. In this context, temporal dynamics matter, and users would greatly profit from ways of identifying the latest design trends. We propose a new way of recommending trending pictures to users, which unfolds in three steps. First, two types of users are identified - those who are good at uploading trends (trend makers) and those who are experienced in discovering trends (trend spotters). Second, based on what those "special few" have uploaded and rated, trends are identified early on. Third, trends are recommended using existing algorithms. Upon the complete longitudinal dataset of the mobile application, we compare our approach's performance to a traditional recommender system's.

Document Doi Bibtex

Title:Spotting trends: The wisdom of the few
Keywords:Mobile, Social Media, Trend Detection
Department:Data Science
Eurecom ref:3759
Copyright: © ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in RECSYS 2012, ACM Recommender Systems Conference, September 9-13, 2012, Dublin, Ireland
Bibtex: @inproceedings{EURECOM+3759, doi = {}, year = {2012}, title = {{S}potting trends: {T}he wisdom of the few}, author = {{S}ha, {X}iaolan and {Q}uercia, {D}aniele and {D}ell'{A}mico, {M}atteo and {M}ichiardi, {P}ietro}, booktitle = {{RECSYS} 2012, {ACM} {R}ecommender {S}ystems {C}onference, {S}eptember 9-13, 2012, {D}ublin, {I}reland}, address = {{D}ublin, {IRELAND}}, month = {09}, url = {} }
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