@article{2017:loosen:making_sen,
title = {Making sense of user comments: Identifying journalists’ requirements for a comment analysis framework},
year = {2017},
note = {Newsrooms are still searching for ways to manage user comments because
of both a desire for professional distance from their audiences and a
lack of analytical tools. This paper presents findings from our
exploratory, interdisciplinary study in journalism research and
computer science that focuses on the algorithmic classification and
clustering of user comments. In contrast to endeavours that aim at
filtering out hate speech or spam, we take a more constructive
approach and focus on detecting particularly useful or high-quality
user contributions that can be leveraged for journalistic purposes. On
the basis of a literature review and our own preliminary research on
audience participation and user review analytics, we developed a
mock-up of a software framework to help journalists systematically
analyze user comments to this end. We then surveyed its effectiveness
through two group discussions - one with comment moderators and
another with editors from different editorial departments of a large
German online newsroom. Features that journalists and comment
moderators considered useful include the categorization of user
comments in pro- and contra-arguments towards a certain topic, the
automated assessment of comments' quality as well as the
identification of surprising or exceptional comments and those that
present new questions, arguments or viewpoints.},
journal = {SCM Studies in Communication and Media},
pages = {333--364},
author = {Loosen, Wiebke and Häring, Marlo and Kurtanović, Zijad and Merten, Lisa and Reimer, Julius and Roessel, Lies van and Maalej, Walid},
volume = {6},
number = {4}
}