Study Finds Negative Sentiment Dominates Responses to the Dilan ITB 1997 Trailer on YouTube
MAKASSAR, Indonesia – Public reactions to the Dilan ITB 1997 movie trailer on YouTube were largely negative, according to a study conducted by Mufidatul Azmi and Nidrah from Universitas Negeri Makassar (UNM). Published in 2026 in the International Journal of Applied and Advanced Multidisciplinary Research (IJAAMR), the research reveals that concerns about character suitability, casting choices, and comparisons with previous Dilan films were the primary drivers of audience criticism. The findings highlight how social media has become more than just a promotional platform for films. Today, online comment sections provide valuable insights into public opinion and can significantly influence how audiences perceive a movie before its release. For filmmakers and marketers, understanding these reactions is increasingly important in shaping successful digital promotion strategies. The study focused on the trailer for Dilan ITB 1997, which was officially released on YouTube on April 3, 2026, ahead of the film’s theatrical debut on April 30. As part of the popular Dilan franchise based on novels by Pidi Baiq, the movie attracted widespread attention from fans who had followed earlier installments such as Dilan 1990, Dilan 1991, and Milea: Suara dari Dilan. The franchise’s previous success created strong emotional connections between audiences and the iconic characters Dilan and Milea, originally portrayed by Iqbaal Ramadhan and Vanesha Prescilla. As a result, expectations for the latest adaptation were exceptionally high. To examine audience perceptions, the researchers collected 3,519 YouTube comments using web-scraping techniques developed in Python through Google Colaboratory. The comments were then cleaned and processed before being analyzed using IndoBERT, an advanced Indonesian-language artificial intelligence model capable of understanding contextual expressions commonly found on social media. In addition to sentiment classification, the researchers applied Latent Dirichlet Allocation (LDA) topic modeling to identify the main themes discussed by viewers. The analysis revealed a clear dominance of negative sentiment among commenters.
Sentiment Distribution
Out of 3,519 comments analyzed:
-1,944 comments (55.2%) were classified as negative.
-939 comments (26.7%) were classified as neutral.
-636 comments (18.1%) were classified as positive.
The large proportion of negative comments suggests that many viewers expressed dissatisfaction with certain aspects of the trailer, particularly regarding casting decisions and character representation.
Main Topics Discussed by Audiences
The topic-modeling results identified several recurring themes in audience conversations.
Negative sentiment topics included:
-Criticism of character suitability.
-Comparisons between new and previous actors.
-Concerns about casting decisions and character portrayal.
Positive sentiment topics included:
-Appreciation for the trailer’s visual quality.
-Support for specific actors and actresses.
-Excitement about the continuation of the Dilan storyline.
Neutral sentiment topics included:
-Discussions about the plot.
-Conversations about characters and actors.
-Speculation regarding future story developments.
One of the study’s most notable findings is the role of nostalgia in shaping audience perceptions. Many viewers continued to associate the character of Dilan with Iqbaal Ramadhan’s portrayal in earlier films. This strong attachment led audiences to compare the new adaptation with previous versions, influencing their overall evaluation of the trailer. The researchers also used word-cloud visualizations to identify frequently used terms within each sentiment category. Negative comments were dominated by words such as “old,” “less,” “student,” and “fit,” indicating concerns about whether the actors matched the audience’s expectations of university student characters. In contrast, positive comments frequently included words such as “cool,” “like,” “the movie,” and “thank you,” reflecting appreciation for the trailer’s presentation, visuals, and the continuation of the Dilan cinematic universe. According to Azmi and Nidrah, YouTube comments represent a powerful form of electronic word-of-mouth (e-WOM). In the digital era, audience discussions on social media can influence public perception, amplify support, or generate criticism that affects a film’s reputation even before its official release. The study also demonstrates how artificial intelligence can help researchers and industry professionals better understand public opinion. By combining sentiment analysis with topic modeling, film producers can gain more objective insights into audience expectations and reactions to promotional content. From a technical perspective, the IndoBERT model performed well in classifying audience sentiment, achieving an overall accuracy rate of 89 percent. The researchers noted that while informal language and contextual nuances remain challenging, the model proved effective in analyzing Indonesian-language social media comments. The findings have broader implications for Indonesia’s film industry. Audience feedback collected through social media platforms can serve as an early indicator of public reception and help production companies refine marketing strategies before a movie reaches theaters. Understanding audience sentiment can also assist filmmakers in addressing viewer expectations and improving communication with fan communities. As digital engagement continues to grow, studies like this provide valuable evidence that online comments are more than casual conversations. They are a rich source of data that can reveal audience preferences, expectations, and concerns, offering important lessons for entertainment marketing in the digital age.
Author Profiles
Mufidatul Azmi, M.I.Kom. is a researcher and academic at Universitas Negeri Makassar (UNM) whose work focuses on digital communication, social media analysis, sentiment analysis, and audience behavior in digital environments.
Nidrah, M.I.Kom. is a lecturer and researcher at Universitas Negeri Makassar (UNM) specializing in mass communication, digital media studies, and the application of technology in communication and digital marketing research.
Research Source
Article Title: Audience Responses Toward Digital Film Promotion on Youtube: A Study of Dilan ITB 1997 Trailer Comments
Authors: Mufidatul Azmi and Nidrah
Journal: International Journal of Applied and Advanced Multidisciplinary Research (IJAAMR)
Volume & Issue: Vol. 4, No. 5
Year: 2026
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