Yesterday once more: collective storytelling and public engagement with digital cultural products on the music streaming platform

This research explores the factors influencing the success of cultural products, specifically songs, on digital music streaming platforms. Existing research often focuses on the characteristics of the message or the source, neglecting the crucial role of audience engagement and the interactive nature of online platforms. This study utilizes the narrative transportation theory, which posits that audience engagement stems from emotional and memory-based involvement in a narrative. The researchers propose that user comments, acting as a form of collective storytelling, amplify the impact of songs by providing additional emotional and autobiographical context. The study's focus is on NetEase Cloud Music, a major platform in China, where user comments are a prominent feature, allowing for a rich understanding of how collective storytelling contributes to a song's popularity and perceived quality.

The study draws heavily on narrative transportation theory, examining its application to digital cultural products. Previous research has explored various factors affecting the influence of cultural products, including source-level factors (e.g., artist characteristics) and message-level factors (e.g., song quality). Studies have used metrics like views, shares, and ratings to gauge popularity. However, the role of user-generated content, particularly comments, in shaping the impact of cultural products on platforms like NetEase Cloud Music, has been relatively under-explored. Existing research also highlights the impact of emotions on media consumption and social sharing, with some studies suggesting that negative emotions can be more effective in promoting engagement than positive ones in certain contexts. The researchers address this gap by focusing on the content and emotions expressed in user comments on a non-Western platform, enriching the existing literature on narrative transportation and the influence of user-generated content on cultural product popularity.

The study collected data from NetEase Cloud Music using a Python crawler. The dataset included information on Chinese singers, their albums, songs, and the top-rated comments for each song (up to 15 comments per song). The researchers focused on Chinese pop songs, gathering data on 7470 singers, 137,546 albums, and 478,864 songs. A total of 1.31 million comments were collected under 187,678 songs. The data included comment text, time, likes, and user information. Text data cleaning involved removing punctuation, numbers, URLs, and non-Chinese characters, followed by stop word removal and word segmentation using the Jieba package. The dependent variables were user engagement (measured by the number of comments, log-transformed for normalization) and perceived quality (measured by NetEase Music's official score, also log-transformed). Independent variables included the number of likes (log-transformed), emotional framing (sentiment polarity and seven basic emotions using BosonNLP and the Chinese Emotional Vocabulary Ontology database), and topics (identified using topic modeling with LDA in Gensim). Control variables were singer type (male, female, band) and album number (log-transformed). Fixed-effect regression models were used to analyze the data.

The analysis revealed several key findings. First, male singers generally elicited more user engagement and higher perceived quality ratings compared to female singers and bands. Surprisingly, artists with more albums had fewer user comments and lower quality ratings, suggesting that increased output doesn't necessarily correlate with increased popularity or perceived quality. The number of likes for comments significantly and positively impacted both user engagement and perceived quality. Regarding lyric content, negative polarity had a negative impact on user engagement but a positive effect on perceived quality. Sadness and nostalgia in lyrics positively influenced both user engagement and quality. Crucially, the study confirmed that user comments significantly impact the song's success. Nostalgia as a topic in comments, along with comments discussing related films/TV shows and singer performances, positively correlated with user engagement and perceived quality. Negative emotions in comments (e.g., negative polarity, sadness, anger, disgust) also positively influenced both variables, although fear had a negative impact. Interaction effects were found between nostalgia in comments and nostalgia/negative polarity in lyrics, showing that the impact of comment nostalgia on engagement and quality is moderated by the emotional and thematic content of the lyrics themselves. The impact of sadness in comments on engagement is also moderated by lyric nostalgia. Notably, less established artists benefitted disproportionately from positive user engagement and comments.

The findings support the hypothesis that user comments, particularly those with autobiographical narratives and negative emotions, significantly increase a song's influence on music streaming platforms. This highlights the importance of audience participation and collective storytelling in shaping the success of cultural products. The study extends the narrative transportation theory by emphasizing the active role of audiences and the impact of user-generated content in a non-Western context. The results also demonstrate that the influence of cultural products is not solely determined by inherent qualities or artist reputation but is significantly shaped by audience interaction and the emotions and memories evoked in these interactions. The finding that emerging artists benefit more from positive user engagement suggests that social media platforms can level the playing field, allowing lesser-known artists to compete with established ones.

This research enhances narrative transportation theory by demonstrating the crucial role of user comments in shaping the success of cultural products on music streaming platforms. The study shows how autobiographical narratives and negative emotions in comments boost song popularity, particularly for emerging artists. Future research could expand to multiple platforms, incorporate musical attributes, include diverse data sources (e.g., user surveys), and explore engagement with foreign music to provide a more comprehensive understanding of online music engagement and the dynamics of cultural product influence.

The study's limitations include its focus solely on NetEase Cloud Music, neglecting potential platform-specific effects. The exclusion of musical attributes and reliance on textual analysis of comments also limits the scope of analysis. The focus on online users who actively comment may not fully represent the broader user base. Lastly, the study is restricted to Chinese songs, excluding insights from cross-cultural comparisons.