What Do Opinion Leaders Share from the New Normal on Twitter?: A Qualitative Content Analysis
The question of what kind of content people share on social media is brought up by the COVID-19 pandemic and new normal policy. The government's well-coordinated campaign and the opposition's harsh comments are two of the reasons Indonesians actively utilize Twitter in relation to the new...
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| Format: | Article |
| Language: | English |
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Universitas Gadjah Mada -Â Faculty of Social and Political Sciences
2022
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| Online Access: | https://repository.ugm.ac.id/283769/1/71844-273506-1-PB.pdf |
| _version_ | 1826050685982998528 |
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| author | Puluhulawa, F.Y. Rajiyem, Rajiyem |
| author_facet | Puluhulawa, F.Y. Rajiyem, Rajiyem |
| author_sort | Puluhulawa, F.Y. |
| collection | UGM |
| description | The question of what kind of content people share on social media is brought up by the COVID-19 pandemic and new normal policy. The government's well-coordinated campaign and the opposition's harsh comments are two of the reasons Indonesians actively utilize Twitter in relation to the new normal. This study intends to characterize and evaluate the presentation of new normal messages by opinion leaders on Twitter between May 16 and 29, 2020, since opinion leaders have historically been the network's active pioneers on a topic. The theories used for this study are self-presentation, opinion leaders, and the social media approach. The accounts of opinion leaders are determined through Drone Emprit's release of Top 100 New Normal Influencers, which then, generated six profiles: @haikalhassan, @harisazhar, @msaiddidu, @ridwankamil, @ismailfahmi, and @kurawa. The qualitative content analysis method was employed in this study with inductive reasoning. The findings revealed seven categories of new normal statements by opinion leaders, which corresponded to three key speech themes: 1) economic issues, 2) the implementation order of new normal life, and 3) negative sentiments. Additionally, we discovered that when opinion leaders create online personas, they do not aim to transcend the most fundamental parts of their backstage selves. Instead, they establish personas and personalities that are based on the same characters from the offline world. Meanwhile, this study suggests how the data might be useful for the Government, to consider the capacity of text-based platforms to help them learn about behaviors and needs during or even post-pandemic. © 2022 The Author(s). |
| first_indexed | 2024-03-14T00:08:30Z |
| format | Article |
| id | oai:generic.eprints.org:283769 |
| institution | Universiti Gadjah Mada |
| language | English |
| last_indexed | 2024-03-14T00:08:30Z |
| publishDate | 2022 |
| publisher | Universitas Gadjah Mada -Â Faculty of Social and Political Sciences |
| record_format | dspace |
| spelling | oai:generic.eprints.org:2837692023-11-22T04:42:32Z https://repository.ugm.ac.id/283769/ What Do Opinion Leaders Share from the New Normal on Twitter?: A Qualitative Content Analysis Puluhulawa, F.Y. Rajiyem, Rajiyem Social Sciences The question of what kind of content people share on social media is brought up by the COVID-19 pandemic and new normal policy. The government's well-coordinated campaign and the opposition's harsh comments are two of the reasons Indonesians actively utilize Twitter in relation to the new normal. This study intends to characterize and evaluate the presentation of new normal messages by opinion leaders on Twitter between May 16 and 29, 2020, since opinion leaders have historically been the network's active pioneers on a topic. The theories used for this study are self-presentation, opinion leaders, and the social media approach. The accounts of opinion leaders are determined through Drone Emprit's release of Top 100 New Normal Influencers, which then, generated six profiles: @haikalhassan, @harisazhar, @msaiddidu, @ridwankamil, @ismailfahmi, and @kurawa. The qualitative content analysis method was employed in this study with inductive reasoning. The findings revealed seven categories of new normal statements by opinion leaders, which corresponded to three key speech themes: 1) economic issues, 2) the implementation order of new normal life, and 3) negative sentiments. Additionally, we discovered that when opinion leaders create online personas, they do not aim to transcend the most fundamental parts of their backstage selves. Instead, they establish personas and personalities that are based on the same characters from the offline world. Meanwhile, this study suggests how the data might be useful for the Government, to consider the capacity of text-based platforms to help them learn about behaviors and needs during or even post-pandemic. © 2022 The Author(s). Universitas Gadjah Mada - Faculty of Social and Political Sciences 2022 Article PeerReviewed application/pdf en https://repository.ugm.ac.id/283769/1/71844-273506-1-PB.pdf Puluhulawa, F.Y. and Rajiyem, Rajiyem (2022) What Do Opinion Leaders Share from the New Normal on Twitter?: A Qualitative Content Analysis. Jurnal Ilmu Sosial dan Ilmu Politik, 26 (2). pp. 183-196. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149456562&doi=10.22146%2fjsp.71844&partnerID=40&md5=f93e165fb0495c3fb1b268d1acd1edc0 |
| spellingShingle | Social Sciences Puluhulawa, F.Y. Rajiyem, Rajiyem What Do Opinion Leaders Share from the New Normal on Twitter?: A Qualitative Content Analysis |
| title | What Do Opinion Leaders Share from the New Normal on Twitter?: A Qualitative Content Analysis |
| title_full | What Do Opinion Leaders Share from the New Normal on Twitter?: A Qualitative Content Analysis |
| title_fullStr | What Do Opinion Leaders Share from the New Normal on Twitter?: A Qualitative Content Analysis |
| title_full_unstemmed | What Do Opinion Leaders Share from the New Normal on Twitter?: A Qualitative Content Analysis |
| title_short | What Do Opinion Leaders Share from the New Normal on Twitter?: A Qualitative Content Analysis |
| title_sort | what do opinion leaders share from the new normal on twitter a qualitative content analysis |
| topic | Social Sciences |
| url | https://repository.ugm.ac.id/283769/1/71844-273506-1-PB.pdf |
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