?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=Deconstructing+the+Filter+Bubble%3A+User%C2%A0Decision-Making%C2%A0and%C2%A0Recommender%C2%A0Systems&rft.creator=Aridor%2C+Guy&rft.creator=Goncalves%2C+Duarte&rft.creator=Sikdar%2C+Shan&rft.description=We+study+a+model+of+user+decision-making+in+the+context+of+recommender+systems+via+numerical+simulation.+Our+model+provides+an+explanation+for+the+findings+of+Nguyen%2C+et.+al+(2014)%2C+where%2C+in+environments+where+recommender+systems+are+typically+deployed%2C+users+consume+increasingly+similar+items+over+time+even+without+recommendation.+We+find+that+recommendation+alleviates+these+natural+filter-bubble+effects%2C+but+that+it+also+leads+to+an+increase+in+homogeneity+across+users%2C+resulting+in+a+trade-off+between+homogenizing+across-user+consumption+and+diversifying+within-user+consumption.+Finally%2C+we+discuss+how+our+model+highlights+the+importance+of+collecting+data+on+user+beliefs+and+their+evolution+over+time+both+to+design+better+recommendations+and+to+further+understand+their+impact.&rft.subject=Filter+Bubbles%2C+Recommender+Systems%2C+Similarity-based+Generalization&rft.publisher=ACM&rft.date=2020-09&rft.type=Proceedings+paper&rft.language=eng&rft.source=+++++In%3A++Proceedings+of+the+14th+ACM+Conference+on+Recommender+Systems.++(pp.+pp.+82-91).++ACM%3A+New+York%2C+NY%2C+USA.+(2020)+++++&rft.format=text&rft.identifier=https%3A%2F%2Fdiscovery.ucl.ac.uk%2Fid%2Feprint%2F10168775%2F1%2FAridor%2520Goncalves%2520Sikdar%25202020%252C%2520Deconstructing%2520the%2520Filter%2520Bubble.pdf&rft.identifier=https%3A%2F%2Fdiscovery.ucl.ac.uk%2Fid%2Feprint%2F10168775%2F&rft.rights=open