| Title |
Emergence of polarized opinions from free association networks
|
|---|---|
| Published in |
Behavior Research Methods, August 2018
|
| DOI | 10.3758/s13428-018-1090-z |
| Pubmed ID | |
| Authors |
Bálint File, Zsolt Keczer, Anna Vancsó, Beáta Bőthe, István Tóth-Király, Márton Hunyadi, Adrienn Ujhelyi, István Ulbert, Júlia Góth, Gábor Orosz |
| 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 "migrant" were collected from two independent and comprehensive samples in Hungary (N1 = 505, N2 = 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 "Refugees" who need help, whereas the negative pole associated asylum seekers with "Violence." 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. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 25% |
| Student > Master | 5 | 21% |
| Student > Ph. D. Student | 3 | 13% |
| Lecturer | 2 | 8% |
| Student > Doctoral Student | 1 | 4% |
| Other | 3 | 13% |
| Unknown | 4 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 9 | 38% |
| Social Sciences | 3 | 13% |
| Unspecified | 1 | 4% |
| Immunology and Microbiology | 1 | 4% |
| Business, Management and Accounting | 1 | 4% |
| Other | 2 | 8% |
| Unknown | 7 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 September 2018.
All research outputs
#2,789,959
of 25,385,509 outputs
Outputs from Behavior Research Methods
#324
of 2,526 outputs
Outputs of similar age
#54,439
of 341,399 outputs
Outputs of similar age from Behavior Research Methods
#12
of 47 outputs
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