SA – Data Cultures

Posted on December 6, 2018 by SA

the good and bad in social media data

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One of the many benefits of social media data which was mentioned in the text (What you can, can’t and shouldn’t do with social media data) by Rachael taxman was how it made making specific studies and statistics much more manageable. What used to take years and sometimes decades can now be done in days and with a fraction of the number of workers. The benefits of social media data are more; it turned out that because of physiological reasons the data collected from social media platforms is more honest and accurate. That is because the information is obtained without any direct contact. Turning to the things that you cannot get from social media data, in the text it mentions that the data collected from the social media will defiantly be biased since you are just examining a particular group and not the whole population of a place. Also, you do not know about whom you are collecting data from. Moreover, there are certain privacy agreements that you have to abide that restricts you. And in the end of course it talked about the ethical aspect of collecting data from social media sites which were mainly about making sure that who ever’s data was taken it should be under all the ethical rules.

I think I agree with HC opinion on how “this should just be another tool researchers use, and not replace all forms of data collection.”

Posted on November 30, 2018 by SA

“THE FAIR DATA PRINCIPLES”

The text is about as said in it “ not to define nor suggest any technological implementation for any of these facets, but rather to define the characteristics, norms, and practices that data resources, tools, and infrastructures should exhibit in order to be considered ‘FAIR.’” .what I got from reading this text is that FAIRness is not a dichotomy but more like a scale. Also, that data FAIRness facets are that data should be Findable, Accessible, Interoperable, and Re-usable. On CM-B’s response, there were points made about how fairness is difficult to achieve because of several reasons, CM-B mentioned two main ones which are that there is “no universal storage of data that ensure that all data recorded is done with unique… identifier” and that “technology advances at different velocities in different parts of the world.”

Posted on November 12, 2018 by SA

Disambiguating places in texts

In the text “Locating Place Names At Scale: Using Natural Language Processing To Identify Geographical Information In Text” the writers discussed the problem of “How might we be able to more accurately predict the exact location using the broader context?”. After they gave the solution to that problem by using computational methods that can predict the exact geolocation of the place mentioned in the text analyzed by its context. Those methods included NER, Google API and FWP. At last, they showed how can that make a difference in the two figures attached to the article.

I think this article was an eye-opener since I have never considered how we should take everything in mind when interpreting our data.

Posted on November 8, 2018 by SA

visual change

Lincoln A. Mullen’s article chose “lynching” as an example to talk about how great visualizing data is. It tells how lynching was a big problem and how it did not get attention until data was visualized. The reason behind that might be what CM-B said in his response, November 8 – Lynching, Visualization, and Visibility, that plain data is not as easy to be absorbed as much as visualized data. Not just that it also shows how after this visualized data many good consequences happened as other studies that fall under injustice, racism and white supremacy.

Posted on October 30, 2018 by SA

the shadows in the archives

This article tells a story that explains the issues of historical labor and how they can forget important people from historical archives or never talking about them with their voices. I found the whole process of developing a “ new set of critical practices “ that suggest that we should “learn to see shadows in the archives” interesting. And this article shows that as my classmate JH said this could be done using digital tools, to gain knowledge about someone or something that is absent in the archival record. Also, another point made in the text that I found important was that “ no piece of writing exist alone. Rather, all texts are bound up in a set of larger social and cultural networks “. It makes me more aware when looking through data or when referencing to it.