Persuasive commentary: using the elaboration likelihood model to predict attitudinal change online
2013
- 1,767Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage1,767
- Downloads1,615
- 1,615
- Abstract Views152
Thesis / Dissertation Description
The current study examined the persuasiveness (based on the Elaboration Likelihood Model) of user comments on the evaluation of an Internet news article. Participants reviewed a news article concerning the implementation of a new comprehensive exam for all senior-level undergraduates, which was manipulated such that the news article information was either self-relevant (evoking central route processing) or self-irrelevant (evoking peripheral route processing). In addition, comments that followed the news article were also manipulated by both strength and quantity. Attitudes toward the topic of comprehensive exams for seniors were assessed via an attitudinal scale and thought listing task after viewing both the news article and subsequent commentary. Because individuals who process information centrally are more likely to parse information for logical development, it was predicted that individuals who centrally process information would be more likely to be influenced by the strength of comments than comment quantity. Alternatively, because individuals who process information peripherally pay attention to peripheral cues in lieu of logical development, it was predicted that these individuals would be more likely to be influenced by comment quantity than comment strength. Results suggested a possible conformity effect in both attitude and thought responses, such that comment presence alone evoked more positive attitudes and positive thoughts toward the proposed exam when compared to a no-comment control group. Additionally, contrary to the ELM, results suggested self-relevance was only a marginally significant factor when comparing attitudinal and thought response differences based on comment strength and a non-significant factor based on comment quantity. Finally, implications of utilizing consensus information (i.e., all pro-issue user comments) as well as caveats regarding the application of the ELM to online contexts are discussed.
Bibliographic Details
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