Emergence of polarized opinions from free association networks

Abstract

We developed a method that can identify polarized public opinions by finding modules in a network of statistically related free word associations. Associations to the cue Bmigrant^were collected from two independent and comprehensive samples in Hungary (N 1 = 505, N 2 = 505). The co-occurrence-based relations of the free word associations reflected emotional similarity, and the modules of the association network were validated with well-established measures. The positive pole of the associations was gathered around the concept of BRefugees^who need help, whereas the negative pole associated asylum seekers with BViolence.^The results were relatively consistent in the two independent samples. We demonstrated that analyzing the modular organization of association networks can be a tool for identifying the most important dimensions of public opinion about a relevant social issue without using predefined constructs.

Mental and emotional representations of “weight loss”: free-word association networks in members of bariatric surgery-related social media communities

“…Further, they had to select two emotions from a list of 20 basic emotions (interest, anxiety, empathy, contempt, surprise, indifference, hope, fear, gratitude, anger, joy, sadness, calmness, frustration, pride, shame, generosity, envy, sympathy, antipathy) that best described their feelings about each of the five associations they provided [16,17]. Emotional labeling was successfully applied in a recent study to improve the interpretation of free-word associations by the addition of affective content [12].…”

“…In order to extract the most prominent mental representations from the numerous individual associations provided by the respondents, we applied an in-house developed algorithm, using a network-based methodology validated and described earlier by our group [12]. To create such a network, nodes (free word associations) and edges (statistical co-occurrences between two associations) were determined.…”

“…: modules) [21]. We have previously demonstrated that these modules of associations -as consistent patterns in individual association sequences -are able to capture the most prominent cognitive representation of a given cue [12]. Associations with weak module attachment were separately identified, since they may serve as bridges in future communicational strategies to simultaneously address individuals with different cognitive modular membership.…”

“…However, due to the sensitive, personal and private nature of patients' perception of their own body weight, direct questions from healthcare professional may be perceived as judgmental or scolding, and may rapidly close down communication [11]. In this sensitive context, an anonymized online survey with a free word association task seems to be an optimal approach to scope group opinion [12].…”

“…We aimed to map the mental and emotional representation of the term weight loss in patients with obesity who had a documented interest in BS, using free word associations combined with a novel data-driven associative analytical method [12]. Further, we aimed to investigate the relationship between these representations and clinical parameters, such as stage of obesity and previous or planned experience with BS.…”