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Public Discourses on AI Companions in Indonesia: A Semantic Network Analysis of Twitter Conversations

Jurnal Komunikasi Ikatan Sarjana Komunikasi Indonesia (JKISKI) · Vol. 11 No. 1 (2026) · pp. 69–77

DOI
10.25008/raapr457
ISSN
2503-0795, 2548-8740
Published
2026-06-04
Publisher
Jurnal Komuniksi ISKI
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The advancement of artificial intelligence (AI) has transformed how humans communicate and make sense of technology. One notable example is ChatGPT, an AI-based conversational system that has become embedded in everyday digital life, functioning not only as a tool but also as a communicative partner. This study aims to map public discourse about ChatGPT on X (Twitter) using a semantic network analysis approach. Data were collected from user posts mentioning the keyword “ChatGPT” during August 2025. The dataset was processed and analyzed in Gephi to calculate degree centrality, betweenness centrality, and modularity, and then qualitatively interpreted through Papacharissi’s (2015) Affective Publics framework. The results reveal two dominant clusters: a functional cluster that emphasizes ChatGPT’s role as a productivity and learning assistant, and an emotional cluster that reflects users’ affective attachment to ChatGPT as a conversational companion that provides empathy and emotional validation. The “ChatGPT” node achieved the highest betweenness centrality, signifying its bridging position between rational and affective dimensions of human–machine communication. Drawing on the Affective Publics perspective, the study concludes that digital public spheres are shaped through technologically mediated emotional resonance and collective storytelling, producing new forms of shared meaning and social connectedness within Indonesia’s digital society.

Collaboration network of the authors

13 authors · 17 co-authorship links · 10 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Gunadarma University
  • STIKOM InterStudi
  • Mercu Buana University
  • Multimedia Nusantara University
  • Medan Area University
  • Universitas Airlangga
  • Universitas Jember
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Endah MurwaniMultimedia Nusantara University1
Syafruddin RitongaMedan Area University1
Mahrani MahraniSTIKOM InterStudi1
Poppy RulianaSTIKOM InterStudi1
Haresti Asysy AmrihaniUniversitas Airlangga1
Nur KholisohMercu Buana University1
Melly RidaryanthiMercu Buana University1
Yusuf Muhamad SaidAffiliation unknown1
Sri WahyuniUniversitas Jember1
Reza Praditya YudhaGunadarma University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2503-0795/works, first harvested 29 Okt 2026, last seen 29 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Public Discourses on AI Companions in Indonesia: A Semantic Network Analysis of Twitter Conversations</dc:title><dc:creator>Suaib, Nadinta Rafifah</dc:creator><dc:creator>Rajab Ritonga</dc:creator><dc:creator>Ningsih, Tri Wahyu Retno</dc:creator><dc:description>&lt;jats:p&gt;The advancement of artificial intelligence (AI) has transformed how humans communicate and make sense of technology. One notable example is ChatGPT, an AI-based conversational system that has become embedded in everyday digital life, functioning not only as a tool but also as a communicative partner. This study aims to map public discourse about ChatGPT on X (Twitter) using a semantic network analysis approach. Data were collected from user posts mentioning the keyword “ChatGPT” during August 2025. The dataset was processed and analyzed in Gephi to calculate degree centrality, betweenness centrality, and modularity, and then qualitatively interpreted through Papacharissi’s (2015) Affective Publics framework. The results reveal two dominant clusters: a functional cluster that emphasizes ChatGPT’s role as a productivity and learning assistant, and an emotional cluster that reflects users’ affective attachment to ChatGPT as a conversational companion that provides empathy and emotional validation. The “ChatGPT” node achieved the highest betweenness centrality, signifying its bridging position between rational and affective dimensions of human–machine communication. Drawing on the Affective Publics perspective, the study concludes that digital public spheres are shaped through technologically mediated emotional resonance and collective storytelling, producing new forms of shared meaning and social connectedness within Indonesia’s digital society.&lt;/jats:p&gt;</dc:description><dc:publisher>Jurnal Komuniksi ISKI</dc:publisher><dc:date>2026-06-04</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.25008/raapr457</dc:identifier><dc:identifier>10.25008/raapr457</dc:identifier><dc:source>Jurnal Komunikasi Ikatan Sarjana Komunikasi Indonesia; Vol 11 No 1 (2026); 69-77</dc:source><dc:source>2503-0795</dc:source><dc:source>2548-8740</dc:source><dc:relation>https://jurnal-iski.or.id/index.php/jkiski/article/download/1520/418</dc:relation><dc:rights>https://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>