  To support efficient, balanced news consumption, merging articles from
diverse sources into one, potentially through crowdsourcing, could alleviate
some hurdles. However, the merging process could also impact annotators'
attitudes towards the content. To test this theory, we propose comparative news
annotation, i.e., annotating similarities and differences between a pair of
articles. By developing and deploying NewsComp -- a prototype system -- we
conducted a between-subjects experiment(N=109) to examine how users'
annotations compare to experts', and how comparative annotation affects users'
perceptions of article credibility and quality. We found that comparative
annotation can marginally impact users' credibility perceptions in certain
cases. While users' annotations were not on par with experts', they showed
greater precision in finding similarities than in identifying disparate
important statements. The comparison process led users to notice differences in
information placement/depth, degree of factuality/opinion, and
empathetic/inflammatory language use. We discuss implications for the design of
future comparative annotation tasks.
