Irwan Dwi Arianto
Universitas Pembangunan Nasional “Veteran” Jawa Timur

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Journal : Proceeding of The International Conference on Economics and Business

Sentiment Analysis #samasamabelajar Public Relations Campaign Based on Big Data on TikTok Farikha Rachmawati; Ahimsa Adi Wibowo; Irwan Dwi Arianto
Proceeding of The International Conference on Economics and Business Vol. 1 No. 2 (2022): Proceeding of The International Conference on Economics and Business
Publisher : Universitas Kristen Indonesia Toraja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/iceb.v1i1.189

Abstract

The purpose of this study is to analyze the sentiment of the #samasamabelajar public relations campaign on TikTok in the period 21 December 2021-2 January 2022. Using a positivistic paradigm. Furthermore, the researcher deepened the data analysis by relating the 10 step PR campaign theory from Anne Gregory and the innovation diffusion theory. quantitative research is carried out by collecting data using Algoritma Tech and ASIGTA sentiment analysis. The results of the big data algorithm analysis show that after the #samasamabelajar campaign, the community produced a total of 975 videos. The government works closely with TikTok through a continuing education campaign, the creation of Tiktokclass and University Class Week. The government provides space for the public to play an active role in producing educational social media content in order to provide a positive image of the government. In addition, TikTok social media is a means of delivering government information to the public. The result sentiment analysis to public's response to the public relations campaign on Tiktok. The researcher conducted a sentiment analysis using the tech algorithm on the search results for the hashtag #samasamasiswa for the period 21 December 2021-2 January 2022. There are 974 hashtags that will be classified using the tech algorithm. Of the 934 videos obtained or analyzed, there were 428 positive content, 533 neutral content and 13 negative content.