Research 701 ~ Credibility
How can something be credible? Both the oxford dictionary and merriam-webster define credibility as “the quality of being believable” [source 1] [source 2] This to me is rather dangerous, since things like vaccine hesitancy have gained traction in recent years. This stems from social platforms giving an amplified voice to those who are not credible, but are accepted as credible by others using the social platform(s) for their source(s) of information. This only brings up the question of how does one know that something is in fact credible?. In my opinion, something becomes credible when established individuals or institutions recognize and iterate or add to an existing/new paradigm or theory. By established I mean any entity that has proven to be knowledgable in the areas they are discussing by citing previous work(s). Even if the paradigm/theory is new or different from the current, it must be based on some sort of factual work.
A lot of information that I personally aquire is from wikipedia, which most people believe to not be a credible source. To an extent I can agree with those people, however I don’t believe the information provided on wikipedia is not credible. This is because most information provided is often cited, and (in most cases) by reputible sources. Of course the information can be provided by any individual, and the individual may not be a credible source, however the source they cite (normally) is.
The tutor gave the class a group project of researching and answering questions on a given reseach methodology. The questions are …
What is it?
What kinds of questions/problems is it useful for?
How can it be used in IT research?
What are strengths?
What are weaknesses?
My group’s methodology is discourse analysis.
What is it?
Discourse analysis is an analysis of language, more specifically around conversations in their social context. It can be used to better understand aspects of communication(s) and “it offers ways of investigating meaning, whether in conversation or in culture.” [source]
What is it useful for?
“Discourse analysis can be used to study inequality in society, such as institutional racism, bias in media, and sexism. It can examine discussions around religious symbols located in public places. Researchers in the field can aid the U.S. government by picking apart speeches by world leaders, such as Syria’s leader Bashar Al-Assad and North Korea’s Kim Jong Un. It can also be used by businesses to quantify hot topics in social media discussions, among other business applications.
In the field of medicine, communication research has examined, for example, how physicians can make sure they’re understood by people with limited English skills or how cancer patients cope with their diagnosis. In one study, transcriptions of conversations between doctors and patients were analyzed to find out where misunderstandings occurred. In another, women were interviewed about their feelings on the first diagnosis, how it affected their relationships, what the role of their social support network was, and how ‘positive thinking’ came into play.” [source]
How can it be used in IT research?
One area that stands out to me which discourse analysis would be extremely useful in is natural language processing or NLP. NLP is a field of computer science which revolves around the interactions between computers and human languages. One of the largest hurdles that computers face when dealing with human languages is normally the context in which the language is portrayed. I believe that discourse analysis can be used to aid in intrepretation of human languages with the given context(s).
What are strengths?
- “Awareness of socio-political and moral implications of psychological research” [source]
- “Take into account the role of historical and socio-political aspects of the research produced” [source]
- “Able to situate itself along the diverse spectrum of epistemological positions, be it realist or relativist” [source]
What are weaknesses?
- “Texts are usually written for a particular audience” [source]
- “Most of the documents that are published are sanitised; that is, they are written in such a way as to iron out any indication of disagreement or contestation” [source]
- “Bias and distortion in that researchers who employ discourse-based methods select evidence that confirms their arguments and ignore contrary data” [source]
- “Over-generalize and infer too much from a particular example” [source]
- “Manifold interpretations as to what ‘discourse’ actually entails” [source]
- “Limited utility in a practical context” [source]