W3 — Peer review
The Article ”Critical Questions for Big Data” by Danah Boyd & Kate Crawford, offers six issues or provocations regarding Big Data. It is discussed how Big Data is not objective despite the enormous amount of data the datasets can contain, and how the size of the datasets is not always the terminating factor of a great research . The issues regarding the ethicality of Big Data is discussed through the argument that all public data should not necessarily be used without consent from the persons behind the construction of the data, and that their data can lose their meaning when taken out of context. The access to Big Data is by the authors seen as being favored to those of wealth and higher social status.
It is clear for the reader that the article is written by researchers, for other researchers — but the way it is described could have been done in a more formal way, without sounding like some areas of studies are better than others, as I feel is written between the lines of these sentences : “We are social scientists and media studies scholars who are in regular conversation with computer scientists and informatics experts. The questions that we ask are hard ones without easy answers, although we also describe different pitfalls that may seem obvious to social scientists but are often surprising to those from different disciplines”.
The language used in the article is well balanced, using academic words without complexifying the text without any reason. The language is also suitable for the audience being from many different backgrounds.
The tone of the language is slightly negative, properly caused by the theme of the article being to show examples of provocations towards Big Data. I can not find a clear example, so maybe it is just my overall feeling that the article is written with a grain of negativity towards the fame Big Data have gotten in recent years.
No introduction to the six examples is given. The readers are thrown right into the first example without knowing if this is seen as a big issue in Big Data or just a random one that have been picked from a raffle .
Structure wise, the article could have used more headlines. It is sometimes unclear what is about to happen next in the paper, as there is no real introduction or transition from section to section. This can especially be seen in the final part of the paper, which I would have called conclusion or final thoughts to mark the ending of an example and the ending of the paper.
Some arguments stated in the article could have benefited from being less provocative against big data, which is demonstrated in this quote. “Big Data researchers with access to proprietary data sets are less likely to choose questions that are contentious to a social media company if they think it may result in their access being cut.” I am pretty sure that this would also be the case of “small data researchers” having access to proprietary data — making the statement vague .
