Hyun Suk Kims’ Research Article Critique Free Essay

Kim, H. S. (2015). Attracting views and going viral: How message features and news-sharing channels affect health news diffusion.

Article summary

In this article, Hyun Suk Kim carried out a study analyzing the real online dissemination of data for the New York Times article for health news including other related articles as well as contextual data. Due to this research’s observational nature, the author found the essentiality of controlling the probable confounders so as to achieve unbiased estimations of message impacts on the selection of news and its retransmission. Precisely, this study opted to use the selection count to be a covariate when making predictions for the sharing count. Kim found news articles with more informational content and positive statements to be inviting more recurring selections and retransmissions. Kim also determined that articles were mostly selected regularly when they talked about controversial issues, emotional evocative issues and familiar contents. Additionally, Kim concluded from his study that informational utility, as well as novelty, possess a stronger positive connotation with email-specified virality whereas emotional evocativeness, familiar content and also exemplification contributed significantly in promoting social media-based transmission. It is difficult to disagree with Kim’s stand, therefore, I agree with him. This paper, criticizes Kim’s theory, method and overall presentation of his arguments in his article.

Article Critique

Kim’s method for carrying out the analysis is quite exceptional and appealing that I tend to agree with. The method of research used here entails, gathering data, using machine-based data collection. I find this appealing because the use of a machine in data mining tends to be more effective and involves minimal errors when collecting data, unlike manual data collection. Moreover, Kim exploited the use of content analysis to analyze the collected data through the use of human and also computerized coding. The combination of both human and computerized coding is a top-notch strategy to use that produces eloquent and actual results for the analysis. I find using these two analysis approaches to be concise and help to reduce errors thus producing actual and real data.  The next step used by Kim is the message evaluation survey to evaluate the effectiveness of the messages. This is a brilliant move by Kim that I agree with. After, collecting and analyzing data, it is important to undertake a survey to assess the effectiveness of messages on people’s behavior. In fact, it adds more weight and evidence by surveying several respondents that read the same article. I like that the author has used multiple respondents from different races and gender. Additionally, emotional positivity has scale has been evaluated in form of sadness, fear, and anger.

The study has used statistical modelling as its theoretical framework for examining its hypothesis. I find this model being effective since it has enabled the study to achieve its objective by examining the objective associated with message effects caused by selection as well as news sharing. This model has enabled to demonstrate the editorial cue in the article to create news importance that subjects its readers to develop emotions. Generally, the study used appropriate control variables which include; seasonal variables, basic linguistic features, teasers that entails disease-specific expressions, message variations associated with content experience and also article category for the New York Times. I find these control variables to be appropriate in guiding the study.

In essence, I tend to agree that the study has been well-framed, an appropriate theoretical framework and methodology used to support the author’s arguments.  The article has eventually met its objective proving that actually messages features, as well as news-disseminating channels, impacts health news dissemination.