fredag 19 september 2014

PRE Theme 3: Research and theory

I chose Journal of Computer-Mediated Communication for the third seminar. It is an Internet based journal about social science research on communicating with computer-based media technologies. It’s interdisciplinary and publishes work from communication, business, education, political science, sociology, psychology, media studies, information science, and other disciplines.

The paper I read was Channeling Science Information Seekers' Attention? A Content Analysis of Top-Ranked vs. Lower-Ranked Sites in Google from the same journal written by Nan Li, Ashley A. Anderson, Dominique Brossard and Dietram A. Scheufele. It says that search engines on the web make larger and more popular websites more appearance and dominant while they discriminate smaller websites, according to researchers. But there is a lack of empirical studies if search engines may favor a certain type of websites. The main questions of this paper are how do the very top results that receive vast public attention portray certain issues? This paper provides a research about how the content in top-ranked websites about nanotechnology differ from websites of lower ranking on Google. The method used was to take samples of the 32 first links, and by a program that’s collect data of the textual contents and by the content of the “child links”, the hyperlinks that are attached to them. The result shows that the top-ranked websites was more about technical function, environmental- and risk related information about nanotechnology. On lower-ranked sites they found that they contained significantly different themes. That shows that Google, as the market leading search engine, has an impact on web based science information.

1. A theory explains why, how and under which circumstances acts, events, structure, and thoughts occur of a certain phenomena. To identify objects of the phenomena and their relations to describe, explain, and enhance understanding of the world. Theory, though, is not references, is not data, is not a list of variables or constructs, is not diagrams and not hypothesis. These are just tools to support a theory.

2. This is a paper consisting a hypothesis, which says that content in the top-ranked websites on Google differ from low ranked websites. This is tested with a case study, to show these results. Therefore I think this is a typical prediction with testable proposition, but no causal explanation.


3. The limits of a prediction theory is the design of the task, and might not meet the expectations of the real world. The data can be wrong, or not enough significantly. The prediction is nor focused on explanation and doesn’t explains why it is like the theory says.

3 kommentarer:

  1. Hej

    Thank you for your reflections. In your article, did the authors discuss the theory/theories they used? From your summary this was not evident. Neither was it evident that the article aimed at predicting rather than explaining results.

    Leif

    SvaraRadera
  2. Hi Magnus,
    Just a question on your article, you wrote that there is a lack of empirical studies if search engines may favor a certain type of website, does that include your article as well? I feel like investing this kind of subject on only nanotechnology-websites might be a bit to narrow to generalize the results. Just like you wrote, the study has testable proportions but no casual explanation so why do you think this article should be classified as predicting instead of explaining?
    Keep up the good work!
    Sofia

    SvaraRadera
  3. I was wondering a little about that you’re writing that data, diagrams etc are not theory. I agree that they are not theory on their own, but can’t you say that they can be part of a theory rather than tools to support the theory?

    SvaraRadera