Replication Data for: Partisan Temporal Selective News Avoidance: Evidence from Online Trace Data

Copy directly We assess the phenomenon of partisan temporal selective avoidance, or individuals dynamically altering their news consumption when news is negative toward their in-party and out-party. Using nine months of online behavioral data (27,648,770 visits) from 2,462 Americans paired with machine learning classifications, we examine whether changing daily news sentiment toward in- and out-party (macro-level) and exposure to articles negative toward in- or out-party during one's browsing session (micro-level) influence news use. We test if partisans change their consumption of (a) news overall, (b) partisan outlets, (c) hard vs. soft news, and (d) individual articles. We find support for partisan temporal selective news avoidance; partisans alter the volume, type, and source of news because of changing news sentiment. On the macro-level, partisan asymmetries emerge, and on the micro-level, negative news about either party reduce news browsing length while increasing hard news and negative news visits for both Democrats and Republicans.from abstract in AJPS publication