2 research outputs found
Don't Let Me Be Misunderstood: Comparing Intentions and Perceptions in Online Discussions
Discourse involves two perspectives: a person's intention in making an
utterance and others' perception of that utterance. The misalignment between
these perspectives can lead to undesirable outcomes, such as misunderstandings,
low productivity and even overt strife. In this work, we present a
computational framework for exploring and comparing both perspectives in online
public discussions.
We combine logged data about public comments on Facebook with a survey of
over 16,000 people about their intentions in writing these comments or about
their perceptions of comments that others had written. Unlike previous studies
of online discussions that have largely relied on third-party labels to
quantify properties such as sentiment and subjectivity, our approach also
directly captures what the speakers actually intended when writing their
comments. In particular, our analysis focuses on judgments of whether a comment
is stating a fact or an opinion, since these concepts were shown to be often
confused.
We show that intentions and perceptions diverge in consequential ways. People
are more likely to perceive opinions than to intend them, and linguistic cues
that signal how an utterance is intended can differ from those that signal how
it will be perceived. Further, this misalignment between intentions and
perceptions can be linked to the future health of a conversation: when a
comment whose author intended to share a fact is misperceived as sharing an
opinion, the subsequent conversation is more likely to derail into uncivil
behavior than when the comment is perceived as intended. Altogether, these
findings may inform the design of discussion platforms that better promote
positive interactions.Comment: Proceedings of The Web Conference (WWW) 202