Incorporating the Measurement of Moral Foundations Theory into Analyzing Stances on Controversial Topics Rezvaneh Rezapour rezapou2@illinois.edu University of Illinois at Urbana-Champaign Champaign, USA Ly Dinh dinh4@illinois.edu University of Illinois at Urbana-Champaign Champaign, USA Jana Diesner jdiesner@illinois.edu University of Illinois at Urbana-Champaign Champaign, USA ABSTRACT This paper investigates the correlation between moral foundations and the expression of opinions in the form of stance on diferent issues of public interest. This work is based on the assumption that the formation of values (personal and societal) and language are interrelated, and that we can observe diferences in points of view in user-generated text data. We leverage the Moral Foundations Theory to expand the scope of stance analysis by examining the narratives in favor or against several topics. Applying an expanded version of the Moral Foundations Dictionary to a benchmark dataset for stance analysis, we capture and analyze the relationships be- tween moral values and polarized online discussions. Using this enhanced methodology, we fnd that each social issue has diferent łmoral and lexical profles.ž While some social issues project more authority related words (Donald Trump), others consists of words related to care and purity (abortion and feminism). Our correlation analysis of stance and morality revealed notable associations be- tween stances on social issues and various types of morality, such as care, fairness, and loyalty, hence demonstrating that there are cer- tain morality types that are more attributed to stance classifcation than others. Overall, our analysis highlights the usefulness of con- sidering morality when studying stance. The diferences observed in various viewpoints and stances highlights linguistic variation in discourse, which may assist in analyzing cultural values and biases in society. CCS CONCEPTS · Computing methodologies → Natural language processing; · Information systems → Information extraction; · Human-centered computing → Collaborative and social computing. KEYWORDS Moral Foundations Theory, stance analysis, social media, contro- versial topics, text analysis Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for proft or commercial advantage and that copies bear this notice and the full citation on the frst page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specifc permission and/or a fee. Request permissions from permissions@acm.org. HT ’21, August 30-September 2, 2021, Virtual Event, Ireland © 2021 Association for Computing Machinery. ACM ISBN 978-1-4503-8551-0/21/08. . . $15.00 https://doi.org/10.1145/3465336.3475112 ACM Reference Format: Rezvaneh Rezapour, Ly Dinh, and Jana Diesner. 2021. Incorporating the Measurement of Moral Foundations Theory into Analyzing Stances on Controversial Topics. In Proceedings of the 32nd ACM Conference on Hypertext and Social Media (HT ’21), August 30-September 2, 2021, Virtual Event, Ireland. ACM, New York, NY, USA, 12 pages. https://doi.org/10.1145/3465336.3475112 1 INTRODUCTION People use social media platforms such as Twitter to share infor- mation, viewpoints and ideas, read the news, be entertained, and connect with others, among other purposes [16]. Online conversa- tions can include discussions of social issues [34, 44], which may feature the expression of opinions, emotions, and polarizing discus- sions among community members. Social issues have some of their roots in subjective perceptions of cultural, societal, and political characteristics and diferences. These personal or group-based dif- ferences in perceptions and beliefs can lead to debates and conficts, which can be deeply divisive and contain biased justifcations [41]. To solve social issues, legislative changes or gradual reforms at the individual, organizational, and societal level might be needed. Online conversations can serve as one among several sources for recognizing opposing points of view, also referred to as stances, which is a necessary ingredient for bridging gaps between groups, facilitating constructive conversations, and mitigating biases. To extract stances, researchers from various felds have lever- aged large amounts of online, user-generated texts and real-time conversations on social media platforms. One direction of scholarly work on this issue, also known as stance analysis, aims to detect people’s position on a topic (in favor or against). Computational solutions for this purpose typically use a combination of linguistic features and machine learning algorithms to build binary classifers [3, 37, 38]. While such approaches are helpful for categorizing peo- ple and terms along stances, in this paper, we study online debates from a diferent perspective, namely by considering morality as an additional independent variable for stance analysis. This work is based on our assumptions that (a) online controversies can have their roots in individual beliefs related to features such as gender and race, political orientation, and other cultural characteristics [1, 46], and (b) people’s everyday language, written or verbal, rep- resents some of these beliefs [52]. Moreover, Moral Foundations Theory (MFT) assumes that emotional and cognitive intuitions, also known as foundations, infuence personal judgements and (moral) decision-making łthrough a psychological preparedness to attend, approve or disapprove particular aspects of situations or issues prior to any conscious reasoning processž [20, 21, 26]. MFT