Fiddler: a visualization prototype interface for making sense of newsfeeds

Algorithms;Algorithm Awareness;Newsfeeds;Hidden Processes

Zhang, Jingning

关键词: Algorithms;    Algorithm Awareness;    Newsfeeds;    Hidden Processes;   

Others  :  https://www.ideals.illinois.edu/bitstream/handle/2142/78514/ZHANG-THESIS-2015.pdf?sequence=1&isAllowed=y

美国|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Our digital life is filled with hidden curation algorithms that are affecting our life. In the FeedVis study [24] with Facebook News Feed, more than half (62.5%) of the users were unaware of the curation algorithm. However, they started manipulating it after they discovered its existence. Multiple cases can also be found where people tried to understand or alter the algorithms with their experiments. Therefore, we built Fiddler, a visualization interface to help users make sense of curation algorithms through comparison. The system has a comparison view and a curation view. The former provides comparison of visual analytic data across time periods to support exploration and goal setting. The latter provides comparison of curated feeds to let users explore their personal curation. With the curation view, we conducted a user study regarding the non-friend Tweets on Twitter. In our study, a non-friend Tweet for a user refers to a Tweet created by someone the user is not following. At the time of our study, the curation algorithm on Twitter displayed all non-friend Tweets retweeted by users’ friends. To study users’ awareness of this algorithm, we listed the latest 200 Tweets in users’ timelines and the non-friend Tweets among them side by side in the curation view. And we found that users were able to tell the non-friend Tweets were mostly Retweets from their friends, which showed their awareness of the curation algorithm. Then we studied users’ satisfaction over the non-friend Tweets, by asking them to label which Tweets they wanted to see. On average, users wanted 27% of non-friend tweets in their timelines. According to users’ explanations, their desired Tweets had interesting, controversial or entertaining topics. Finally, users reported they would like to curate their timeline through unfollowing Twitter connections after this study. With Fiddler, we hope to encourage users to explore curation algorithms and help researchers understand how users want to curate their feeds.