Research on Short Video's Information Attributes and Communication Effect on Mobile Social Media

ZHANG Zixuan, LI Bing, LI Zheng

Chinese Journal of Journalism & Communication ›› 2025, Vol. 47 ›› Issue (4) : 118-133.

PDF(1587 KB)
PDF(1587 KB)
Chinese Journal of Journalism & Communication ›› 2025, Vol. 47 ›› Issue (4) : 118-133.
Research Articles

Research on Short Video's Information Attributes and Communication Effect on Mobile Social Media

Author information +
History +

Abstract

The findings regarding the relationship between information attributes and communication effects on social media have predominantly been derived from textual information in previous research, while video information in the form of audiovisual symbols remains an area in need of further exploration. Questions such as: What is the relationship between its information attributes and communication effects? How do its formal and content characteristics intertwine to influence communication outcomes? —have yet to be fully addressed. This study conducts a full-sample analysis of short video content related to the 2017 NPC & CPPCC released by the official accounts of three central mainstream media outlets on Weibo. Employing computer-assisted and manual coding for content analysis, combined with participatory observation, the study examines the relationships between the communication effects and three dimensions of short video information, including the textual features of video titles, content characteristics, and audiovisual format attributes. Findings reveal that short videos with better communication effects tend to convey positive, equitable, and stable informational attributes. Compared to previous studies based on textual information, video information aligns more closely with the social attributes of social media, such as information communication and emotional management. However, the positive impact of formal features remains limited.

Key words

Information attributes / views / short video / mobile social media / NPC & CPPCC

Cite this article

Download Citations
ZHANG Zixuan , LI Bing , LI Zheng. Research on Short Video's Information Attributes and Communication Effect on Mobile Social Media[J]. Chinese Journal of Journalism & Communication. 2025, 47(4): 118-133

References

[1]
安德烈·巴赞(1958/2005).《电影是什么? (崔君衍译). 江苏教育出版社.
[2]
陈晓东(2012).《基于情感词典的中文微博情感倾向分析研究》.华中科技大学硕士论文.
[3]
大卫·波德维尔, 克里斯汀·汤普森(1997/2003). 《电影艺术——形式与风格》(彭吉象等译)(第5版). 北京大学出版社.
[4]
邸鹏, 段利国(2015). 基于复杂句式的文本情感倾向性分析. 《计算机应用与软件》,(11),57-61.
[5]
高崇, 杨伯溆(2016). 微视频的内容生产模式解析——基于新浪微博官方短视频应用“秒拍”的研究. 《新闻界》,(23),60-65.
[6]
梁胜(2014).《中文微博的情感分析和应用》.南京邮电大学硕士论文.
[7]
陆绍阳(2009). 《视听语言》. 北京大学出版社.
[8]
史伟, 王洪伟, 何绍义(2012). 基于知网的模糊情感本体的构建研究. 《情报学报》,(6),595-602.
[9]
微博数据中心(2016年12月23日).《2016微博用户发展报告》. http://weibo.com/2205075871/Ens0FnE1s?type=comment#_rnd1492908678262.2016.12.
[10]
许小可, 胡海波, 张伦, 王成军(2015). 《社交网络上的计算传播学》. 高等教育出版社.
[11]
杨嫚, 王凯(2016). 基于移动社交网的视频新闻生产策略——以英斯达法克斯(Instafax)为例. 《中国出版》,(3),6-9.
[12]
张梓轩, 雷建军(2013). 在召唤大众中传递主流媒体正能量——论微博版《人民日报》语言传播方式的转变. 《中国出版》,(9),34-36.
[13]
张梓轩, 梁君健(2017). 因袭与重塑:移动传播时代的新闻视听语言特征研究. 《新闻大学》,(5),52-60+148.
[14]
赵云泽, 张竞文, 谢文静, 俞炬昇(2015). “社会化媒体”还是“社交媒体”?——一组至关重要的概念的翻译和辨析. 《新闻记者》,(6),63-66.
[15]
周翔(2014). 《传播学内容分析研究与应用》. 重庆大学出版社.
[16]
Berger J., & Milkman K. L. (2012). What makes online content viral? Journal of Marketing Research, 49(2), 192-205.
Why are certain pieces of online content (e.g., advertisements, videos, news articles) more viral than others? This article takes a psychological approach to understanding diffusion. Using a unique data set of all the New York Times articles published over a three-month period, the authors examine how emotion shapes virality. The results indicate that positive content is more viral than negative content, but the relationship between emotion and social transmission is more complex than valence alone. Virality is partially driven by physiological arousal. Content that evokes high-arousal positive (awe) or negative (anger or anxiety) emotions is more viral. Content that evokes low-arousal, or deactivating, emotions (e.g., sadness) is less viral. These results hold even when the authors control for how surprising, interesting, or practically useful content is (all of which are positively linked to virality), as well as external drivers of attention (e.g., how prominently content was featured). Experimental results further demonstrate the causal impact of specific emotion on transmission and illustrate that it is driven by the level of activation induced. Taken together, these findings shed light on why people share content and how to design more effective viral marketing campaigns.
[17]
Bobkowski P. S. (2015). Sharing the news: Effects of informational utility and opinion leadership on online news sharing. Journalism & Mass Communication Quarterly, 92(2), 320-345.
[18]
Conway M. (2015). “See it now”:Television news. In J. E. Hill & V. R. Schwartz (Eds.), Getting the picture: The visual culture of the news (pp. 168-175). Routledge.
[19]
Dafonte-Gómez A. (2014). The key elements of viral advertising. From motivation to emotion in the most shared videos. ArXiv, abs/1505.02002.
[20]
DeVito M. A., Birnholtz J., & Hancock J. T.(2017, February 25-March 1). Platforms, people, and perception: Using affordances to understand self-presentation on social media [Paper presentation]. The 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, Portland, OR, United States.
[21]
Eisenstein S., & Leyda J. (1949). Film form: Essays in film theory. Meridian Books.
[22]
Godes D., Mayzlin D., Chen Y. et al. (2005), The firm's management of social interactions. Marketing Letters, 16(3-4), 415-428.
[23]
Hall S. (1980). Encoding/decoding. In S. Hall et al (Eds.), Culture, media, language: Working papers in cultural studies, 1972-79 (pp. 117-127). Routledge.
[24]
Heimbach I., & Hinz O. (2016), The impact of content sentiment and emotionality on content virality. International Journal of Research in Marketing, 33(3), 695-701.
[25]
Kim H. S., Lee S., Cappella J. N. et al. (2013). Content characteristics driving the diffusion of antismoking messages: Implications for cancer prevention in the emerging public communication environment. Journal of the National Cancer Institute Monographs, 2013 (47), 182-187.
[26]
Kim H. S. (2015). Attracting views and going viral: How message features and news-sharing channels affect health news diffusion. Journal of Communication, 65(3), 512-534.
This study examined how intrinsic as well as perceived message features affect the extent to which online health news stories prompt audience selections and social retransmissions, and how news-sharing channels (e-mail vs. social media) shape what goes viral. The study analyzed actual behavioral data on audience viewing and sharing of health news articles, and associated article content and context data. News articles with high informational utility and positive sentiment invited more frequent selections and retransmissions. Articles were also more frequently selected when they presented controversial, emotionally evocative, and familiar content. Informational utility and novelty had stronger positive associations with e-mail-specific virality, while emotional evocativeness, content familiarity, and exemplification played a larger role in triggering social media-based retransmissions.
[27]
Lakkaraju H., McAuley J., & Leskovec J. (2013). What's in a name? Understanding the interplay between titles, content, and communities in social media. Proceedings of the International AAAI Conference on Web and Social Media, 7(1), 311-320.
[28]
Lerman K., & Ghosh R. (2010). Information contagion: An empirical study of the spread of news on digg and twitter social networks. Proceedings of the International AAAI Conference on Web and Social Media, 4(1), 90-97.
[29]
Mamula T. (2013). Cinema and language loss displacement, visuality and the filmic image. Routledge.
[30]
Moriarty C. M., & Stryker J. E. (2008). Prevention and screening efficacy messages in newspaper accounts of cancer. Health Education Research, 23(3), 487-498.
The news media are a primary source of cancer prevention and detection information for the general public, but little is known about the content of cancer prevention and detection messages in mainstream media. This study examines how cancer prevention and screening efficacy messages are presented in cancer news media coverage. Efficacy messages provide information about skills related to prevention and screening behaviors. Analysis of cancer-related stories in 44 major US daily newspapers during 2003 (n = 2448) reveals that efficacy messages were rarely present in cancer stories. Efficacy messages were less likely to appear in stories that had a 'local' angle, but efficacy messages were more likely to appear in stories that contained 'mobilizing information' (additional resources for readers) or stories that mentioned highly preventable cancers (lung, skin, esophagus and bladder). The discussion includes a theory of norms for effectively influencing cancer-related behaviors through news reports. Implications of this work extend to the lack of efficacy messages when highly detectable cancers are mentioned, thus the lack of actionable information when health risks are presented, and a dearth of efficacy messages when localized information is present, each of which represent key areas for encouraging health journalists to include more efficacy statements.
[31]
Nelson-Field K., Riebe E., & Newstead K. (2013). The emotions that drive viral video. Australasian Marketing Journal (AMJ), 21(4), 205-211.
[32]
Nilśen V. S. (1959/1972). The cinema as a graphic art. (S., Garry, Trans.). Hill and Wang.
[33]
Ohara K., Saito K., Kimura M., & Motoda H. (2012, April 3-5). Effect of in/out-degree correlation on influence degree of two contrasting information diffusion models [Paper presentation]. International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, College Park, MD, USA.
[34]
Pang B., & Lee L. (2008). Opinion mining and sentiment analysis. Now Foundations and Trends.
[35]
Romero D. M., Meeder B., & Kleinberg J. (2011, March 28-April 1). Differences in the mechanics of information diffusion across topics: idioms, political hashtags, and complex contagion on twitter [Paper presentation]. Proceedings of the 20th International Conference on World Wide Web, Hyderabad, India.
[36]
Shoemaker P. J., Danielian L. H., & Brendlinger N. (1991). Deviant acts, risky business and US interests: The newsworthiness of world events. Journalism Quarterly, 68(4), 781-795.
Significant events happen daily around the world, but only some of these are reported in the U.S. news media. A content analysis of the New York Times, and ABC, CBS, and NBC found that the Times covered only about a fourth of a sample of world events and the networks mentioned only about a tenth. This study finds that events which are deviant in certain ways from U.S. national values and which occur in nations of political and economic significance to the United States are more likely to be covered in the news.
[37]
Song G., Li Z., & Tu H. (2012, May 23-25). Forward or ignore: User behavior analysis and prediction on microblogging [Paper presentation]. Proceedings of the 2012 IEEE 16th International Conference on Computer Supported Cooperative Work in Design (CSCWD), Wuhan, China.
[38]
Tan C., Lee L., & Pang B. (2014) The effect of wording on message propagation:Topic- and author-controlled natural experiments on twitter. In K. Toutanova & H. Wu (Eds.), Proceedings of the 52nd annual meeting of the association for computational linguistics (volume 1: long papers) (pp. 175-185). Association for Computational Linguistics.
[39]
Thompson K., & Bordwell D. (2003). Film history: an introduction (2nd edition). McGraw-Hill.
[40]
Vogelbacker K., Dillahunt X., & McCollum D., (2014, March 4-7). The path from new to viral: Understanding what makes videos go viral [Paper presentation]. iConference 2014 Proceedings, Berlin, Germany.
PDF(1587 KB)

Accesses

Citation

Detail

Sections
Recommended

/