Publication | Open Access
Recommenders with a Mission
77
Citations
44
References
2021
Year
Unknown Venue
Artificial IntelligenceCommunicationJournalismComputational Social ScienceSocial MediaInformation RetrievalData ScienceRecommender SystemsNews AnalyticsFilter BubblesLanguage StudiesContent AnalysisNews RecommendersPredictive AnalyticsKnowledge DiscoveryPersonalized SearchCold-start ProblemInformation Filtering SystemGroup RecommendersInteractive MarketingArtsCollaborative Filtering
News recommenders help users to find relevant online content and have the potential to fulfill a crucial role in a democratic society, directing the scarce attention of citizens towards the information that is most important to them. Simultaneously, recent concerns about so-called filter bubbles, misinformation and selective exposure are symptomatic of the disruptive potential of these digital news recommenders. Recommender systems can make or break filter bubbles, and as such can be instrumental in creating either a more closed or a more open internet. Current approaches to evaluating recommender systems are often focused on measuring an increase in user clicks and short-term engagement, rather than measuring the user's longer term interest in diverse and important information.
| Year | Citations | |
|---|---|---|
Page 1
Page 1