skip to main content

Title: 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 more » 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. « less
Authors:
; ;
Award ID(s):
1910147 1750615
Publication Date:
NSF-PAR ID:
10176520
Journal Name:
Proceedings of WWW
Page Range or eLocation-ID:
2066 to 2077
Sponsoring Org:
National Science Foundation
More Like this
  1. Both liberals and conservatives believe that using facts in political discussions helps to foster mutual respect, but 15 studies—across multiple methodologies and issues—show that these beliefs are mistaken. Political opponents respect moral beliefs more when they are supported by personal experiences, not facts. The respect-inducing power of personal experiences is revealed by survey studies across various political topics, a field study of conversations about guns, an analysis of YouTube comments from abortion opinion videos, and an archival analysis of 137 interview transcripts from Fox News and CNN. The personal experiences most likely to encourage respect from opponents are issue-relevant and involve harm. Mediation analyses reveal that these harm-related personal experiences increase respect by increasing perceptions of rationality: everyone can appreciate that avoiding harm is rational, even in people who hold different beliefs about guns, taxes, immigration, and the environment. Studies show that people believe in the truth of both facts and personal experiences in nonmoral disagreement; however, in moral disagreements, subjective experiences seem truer (i.e., are doubted less) than objective facts. These results provide a concrete demonstration of how to bridge moral divides while also revealing how our intuitions can lead us astray. Stretching back to the Enlightenment, philosophers andmore »scientists have privileged objective facts over experiences in the pursuit of truth. However, furnishing perceptions of truth within moral disagreements is better accomplished by sharing subjective experiences, not by providing facts.« less
  2. Abstract

    Does information about how other people feel about COVID-19 vaccination affect immunization intentions? We conducted preregistered survey experiments in Great Britain (5,456 respondents across 3 survey waves from September 2020 to February 2021), Canada (1,315 respondents in February 2021), and the state of New Hampshire in the United States (1,315 respondents in January 2021). The experiments examine the effects of providing accurate public opinion information to people about either public support for COVID-19 vaccination (an injunctive norm) or public beliefs that the issue is contentious. Across all 3 countries, exposure to this information had minimal effects on vaccination intentions even among people who previously held inaccurate beliefs about support for COVID-19 vaccination or its perceived contentiousness. These results suggest that providing information on public opinion about COVID vaccination has limited additional effect on people’s behavioral intentions when public discussion of vaccine uptake and intentions is highly salient.

  3. Online forums are an integral part of modern day courses, but motivating students to participate in educationally beneficial discussions can be challenging. Our proposed solution is to initialize (or “seed”) a new course forum with comments from past instances of the same course that are intended to trigger discussion that is beneficial to learning. In this work, we develop methods for selecting high-quality seeds and evaluate their impact over one course instance of a 186-student biology class. We designed a scale for measuring the “seeding suitability” score of a given thread (an opening comment and its ensuing discussion). We then constructed a supervised machine learning (ML) model for predicting the seeding suitability score of a given thread. This model was evaluated in two ways: first, by comparing its performance to the expert opinion of the course instructors on test/holdout data; and second, by embedding it in a live course, where it was actively used to facilitate seeding by the course instructors. For each reading assignment in the course, we presented a ranked list of seeding recommendations to the course instructors, who could review the list and filter out seeds with inconsistent or malformed content. We then ran a randomized controlledmore »study, in which one group of students was shown seeds that were recommended by the ML model, and another group was shown seeds that were recommended by an alternative model that ranked seeds purely by the length of discussion that was generated in previous course instances. We found that the group of students that received posts from either seeding model generated more discussion than a control group in the course that did not get seeded posts. Furthermore, students who received seeds selected by the ML-based model showed higher levels of engagement, as well as greater learning gains, than those who received seeds ranked by length of discussion.« less
  4. Anonymity can enable both healthy online interactions like support-seeking and toxic behaviors like hate speech. How do online service providers balance these threats and opportunities? This two-part qualitative study examines the challenges perceived by open collaboration service providers in allowing anonymous contributions to their projects. We interviewed eleven people familiar with organizational decisions related to privacy and security at five open collaboration projects and followed up with an analysis of public discussions about anonymous contribution to Wikipedia. We contrast our findings with prior work on threats perceived by project volunteers and explore misalignment between policies aiming to serve contributors and the privacy practices of contributors themselves.
  5. The purpose of this study is to develop an instrument to measure student perceptions about the learning experiences in their online undergraduate engineering courses. Online education continues to grow broadly in higher education, but the movement toward acceptance and comprehensive utilization of online learning has generally been slower in engineering. Recently, however, there have been indicators that this could be changing. For example, ABET has accredited online undergraduate engineering degrees at Stony Brook University and Arizona State University (ASU), and an increasing number of other undergraduate engineering programs also offer online courses. During this period of transition in engineering education, further investigation about the online modality in the context of engineering education is needed, and survey instrumentation can support such investigations. The instrument presented in this paper is grounded in a Model for Online Course-level Persistence in Engineering (MOCPE), which was developed by our research team by combining two motivational frameworks used to study student persistence: the Expectancy x Value Theory of Achievement Motivation (EVT), and the ARCS model of motivational design. The initial MOCPE instrument contained 79 items related to students’ perceptions about the characteristics of their courses (i.e., the online learning management system, instructor practices, and peer support),more »expectancies of course success, course task values, perceived course difficulties, and intention to persist in the course. Evidence of validity and reliability was collected using a three-step process. First, we tested face and content validity of the instrument with experts in online engineering education and online undergraduate engineering students. Next, the survey was administered to the online undergraduate engineering student population at a large, Southwestern public university, and an exploratory factor analysis (EFA) was conducted on the responses. Lastly, evidence of reliability was obtained by computing the internal consistency of each resulting scale. The final instrument has seven scales with 67 items across 10 factors. The Cronbach alpha values for these scales range from 0.85 to 0.97. The full paper will provide complete details about the development and psychometric evaluation of the instrument, including evidence of and reliability. The instrument described in this paper will ultimately be used as part of a larger, National Science Foundation-funded project investigating the factors influencing online undergraduate engineering student persistence. It is currently being used in the context of this project to conduct a longitudinal study intended to understand the relationships between the experiences of online undergraduate engineering students in their courses and their intentions to persist in the course. We anticipate that the instrument will be of interest and use to other engineering education researchers who are also interested in studying the population of online students.« less