Semantic networks of interests in online non-suicidal self-injury communities
People who engage in non-suicidal self-injury (NSSI) often conceal their practices, which limits examination and understanding of their engagement. The goal of this research is to utilize data from public online social networks (namely, LiveJournal, a major blogging social networking site) to observ...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2016-04-01
|
| Series: | Digital Health |
| Online Access: | https://doi.org/10.1177/2055207616642118 |
| _version_ | 1818559164134195200 |
|---|---|
| author | D Zinoviev D Stefanescu G Fireman L Swenson |
| author_facet | D Zinoviev D Stefanescu G Fireman L Swenson |
| author_sort | D Zinoviev |
| collection | DOAJ |
| description | People who engage in non-suicidal self-injury (NSSI) often conceal their practices, which limits examination and understanding of their engagement. The goal of this research is to utilize data from public online social networks (namely, LiveJournal, a major blogging social networking site) to observe the NSSI population in a naturally occurring setting. Specifically, the focus of this paper is the interests publicly declared by LiveJournal users. In the course of study, we collected the self-declared interests of 25,000 users who are members of or participate in 139 NSSI-related communities. We constructed a family of semantic networks of interests based on their similarity. The semantic networks are structured and contain several dense clusters—semantic domains—that include NSSI-specific interests (such as self-injury and razor ), references to music performers (such as evanescence ), and general daily life and creativity related interests (such as poetry and friendship ). Assuming users are genuine in their declarations, the clusters reveal distinct patterns of interest and may signal keys to NSSI. |
| first_indexed | 2024-12-14T00:21:49Z |
| format | Article |
| id | doaj.art-21284ac7a90440ed9cd5aa48bb7284c1 |
| institution | Directory Open Access Journal |
| issn | 2055-2076 |
| language | English |
| last_indexed | 2024-12-14T00:21:49Z |
| publishDate | 2016-04-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Digital Health |
| spelling | doaj.art-21284ac7a90440ed9cd5aa48bb7284c12022-12-21T23:25:11ZengSAGE PublishingDigital Health2055-20762016-04-01210.1177/2055207616642118Semantic networks of interests in online non-suicidal self-injury communitiesD Zinoviev0D Stefanescu1G Fireman2L Swenson3Department of Mathematics and Computer Science, Suffolk University, Boston, USADepartment of Mathematics and Computer Science, Suffolk University, Boston, USADepartment of Psychology, Suffolk University, Boston, USADepartment of Psychology, Suffolk University, Boston, USAPeople who engage in non-suicidal self-injury (NSSI) often conceal their practices, which limits examination and understanding of their engagement. The goal of this research is to utilize data from public online social networks (namely, LiveJournal, a major blogging social networking site) to observe the NSSI population in a naturally occurring setting. Specifically, the focus of this paper is the interests publicly declared by LiveJournal users. In the course of study, we collected the self-declared interests of 25,000 users who are members of or participate in 139 NSSI-related communities. We constructed a family of semantic networks of interests based on their similarity. The semantic networks are structured and contain several dense clusters—semantic domains—that include NSSI-specific interests (such as self-injury and razor ), references to music performers (such as evanescence ), and general daily life and creativity related interests (such as poetry and friendship ). Assuming users are genuine in their declarations, the clusters reveal distinct patterns of interest and may signal keys to NSSI.https://doi.org/10.1177/2055207616642118 |
| spellingShingle | D Zinoviev D Stefanescu G Fireman L Swenson Semantic networks of interests in online non-suicidal self-injury communities Digital Health |
| title | Semantic networks of interests in online non-suicidal self-injury communities |
| title_full | Semantic networks of interests in online non-suicidal self-injury communities |
| title_fullStr | Semantic networks of interests in online non-suicidal self-injury communities |
| title_full_unstemmed | Semantic networks of interests in online non-suicidal self-injury communities |
| title_short | Semantic networks of interests in online non-suicidal self-injury communities |
| title_sort | semantic networks of interests in online non suicidal self injury communities |
| url | https://doi.org/10.1177/2055207616642118 |
| work_keys_str_mv | AT dzinoviev semanticnetworksofinterestsinonlinenonsuicidalselfinjurycommunities AT dstefanescu semanticnetworksofinterestsinonlinenonsuicidalselfinjurycommunities AT gfireman semanticnetworksofinterestsinonlinenonsuicidalselfinjurycommunities AT lswenson semanticnetworksofinterestsinonlinenonsuicidalselfinjurycommunities |