"A Tale Of Two Internet News Platforms": Real Vs. Fake

A Tale of Two Internet News Platforms -Real vs. Fake: An Elaboration Likelihood Model Perspective

Babajide Osatuyi and Jerald Hughes collaborated together research paper called, “A Tale of Two Internet News Platforms -Real vs. Fake: An Elaboration Likelihood Model Perspective”. Their paper was published on January 3, 2018, so this is about as recent as a research paper can be about Fake News! Our first author, Babajide Osatuyi has his BS, from the University of New York in 2008, with a major in Computer Science. He later received another BS from the University of New York with a major in Computational Science. He later received his PhD from the New Jersey Institute of Technology, with a major in Information Systems.

Babajide Osatuyi, is currently teaching at The University of Texas Rio Grande Valley. On the other hand, Jerald Hughes, who also teaches The University of Texas Rio Grande Valley, received his PhD, at The City University of New York, 2006. His DMA, at University of Kentucky, 1991. His BM, at Rice University in 1985, and MM, at Rice University in 1985. The authors tested four hypotheses in total, and although each test was thorough, and the researchers did plenty of things well, there are still discrepancies throughout the research paper. The two authors set out to test multiple hypotheses about fake news. They had four different hypotheses; the amounts of information presented in posts on fake news platforms will be lower than those of real news, the variances of amounts of information presented in posts on fake news platforms will be lower than those of real news.

The negative valence of information presented in the full texts of posts on fake news platforms will be higher than that presented on real news platforms, and the negative valence of the vocabularies used in posts on fake news platforms will be higher than those used on real news platforms. For their first hypothesis, the authors wanted to see if Fake News sites had, overall, less information in their articles/posts. To test this, the authors used the ELM theory that provides for the presentation of limited information, and focuses on specific, usually irrelevant, cues of the news platform. The ELM theory stands for; Elaboration Likelihood Model. The ELM theory is a dual process theory describing the change of attitudes; like fake news. The researchers then tested their second hypothesis; that the amount of information posted on fake news platforms will be lower than that of real news platforms.

The authors stated that they wanted to test the difference in the variances of information in posts between fake news platforms and real news platforms. The authors came to the conclusion that, on average, real news platforms are more focused on communicating the important information as facts, as compared to fake news platforms, which focus on the emotional aspect and try to tell more of a story. For their third hypothesis, the authors wanted to see if the negative valence of information presented in the full texts of posts on fake news platforms will be higher than that presented on real news platforms.

Babajide and Jerald stated, “As a related indicator of negative valence, we theorize that not only will fake news sites have higher negative valence scores in the full texts of the posts; they will also depend systematically on vocabularies which have higher negative valence than those of real news posts.”. In layman's terms, they theorized that fake news posts will overall have a more negative tone then real news platforms. They tested their hypothesis by making a lost of 4783 terms of negativity, and for each post, on both real and fake news platforms, they counted the amount of negative terms in the article/post. The authors also wanted to test one more hypothesis; that the negative valence of the vocabularies used in posts on fake news platforms will be higher than those used on real news platforms.

The authors stated, “We provided a related but distinct analysis, in this case scoring the vocabularies of each post, instead of the full texts. The procedures were otherwise the same.”. Meaning, they the authors followed the same steps as stated in their third hypothesis, but they tested it on the negative valences of vocabularies, not full texts; as they did in hypothesis three. Babajide Osatuyi and Jerald Hughes hypotheses; Information amounts, New Variances, Negative Valences of full tests, and Negative Valences of vocabularies, were supported in their findings. Overall, it is very easy to see how fake news platforms can have a negative effect on society and businesses. One can say that fake news can spread easily due to its emphasis on negative verbiage, drastic vocabulary and “click-baity” articles that can bring in readers.

The authors, Babajide Osatuyi and Jerald Hughes, did many things well, not only when it came to their research, but also in the way they formatted their research paper. The authors did a good job providing a very detailed, step by step, methodology that for the most part is pretty easy to follow. At times, throughout the paper the reader may be a little confused on a theory used to test one of the reachers hypotheses. Also, when reviewing the hypotheses, one can say that the four hypotheses can easily be condensed into two hypotheses. One can easily combine hypotheses one and two and have it state; The amount of information represented on fake news platforms will be lower than the amount of information used in real news platforms. Overall, the collaberation between Babajide Osatuyi and Jerald Hughes has proven itself worthy of an in depth research article about fake news compared to real news platforms.

Works Cited:

1. Osatuyi , Babajide, and Jerald Hughes. “A Tale of Two Internet News Platforms-Real vs. Fake: An Elaboration Likelihood Model Perspective.” Language Documentation & Conservation, 1(1), June 2007.
2. Ethics and Revitalization of Dormant Languages: The Mutsun Language, University of Hawai'i Press, 3 Jan. 2018, scholarspace.manoa.hawaii.edu/handle/10125/50388.