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## <span class="censor">Data Studies 2021 // S09. Research Issues</span>

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<img src="https://i.imgur.com/O47Gahu.png" width="100%">

Pablo Velasco [pablov.me](https://pablov.me)  & Midas Nouwens // Information Studies

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## Plan for the day:

1. mini-project aftermath
2. Issues/challenges of (digital) research
3. An example of questionable research
4. Formulating a research question
5. Term project basics

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## mini-PROJECT

https://miro.com/app/board/o9J_lm-VFRo=/?invite_link_id=434428915736 

1. What was the most (internally (i.e., coming from them)/externally (i.e., coming from the outside world)) challenging aspect of the mini-project?

2. What was the most surprising aspect of the project?

3. How confident are you that what you 'found' in the data is an accurate reflection of 'reality'?

4. If there is one thing you could tell yourself before starting the mini-project, what would it be?

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MENTI: https://www.menti.com/ko3pe6mwkz

code "**9992 6280**"

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<img src="https://i.imgur.com/fnkVfrg.png" width="49%">

<img src="https://i.imgur.com/xqPGL5J.png" width="49%">

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![](https://i.imgur.com/DwWnGuw.png)


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# ISSUES OF <span style="color:hotpink">(DIGITAL)</span> RESEARCH

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* Digital technologies enable new practices for recording, analyzing, and visualizing social life.
<span class="refs">Fielding, N. G. (2008). The Internet as Research Medium.</span>

<img src="https://hackmd.io/_uploads/HyTFfOn8D.jpg" width="40%">

* optimistic (e.g. Latour via Tarde's sociology) and pesimistic approaches (e.g. <span class="refs">Savage, M., & Burrows, R. (2007). The Coming Crisis of Empirical Sociology. Sociology</span>)

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## The *computational turn*

<img src="https://i.imgur.com/i6xmUsm.png" width="65%">

<span class="refs">Berry, D. M. (2011). The Computational Turn: Thinking About the Digital Humanities</span>

Importance of *devices* as both: 
* the *materials* of social life
*  the *apparatuses* to know it

<span class="refs">Ruppert, E., Law, J., & Savage, M. (2013). Reassembling social science methods: The challenge of digital devices</span>

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<img src="https://i.imgur.com/DOjpGl5.png" width="70%">

<img src="https://i.imgur.com/VCb3ylE.png" width="50%">

"These [computational] subtractive methods of understanding reality (episteme) produce new knowledges and methods for the control of reality (techne)"
 
<span class="refs">Berry, D. M. (2011). The Computational Turn: Thinking About the Digital Humanities</span>

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Need to develop **methodological frameworks** to **reflexively account** for the strengths and weaknesses of both the **technical practices** and the **claims** produced through computational systems

<span class="refs">Elish, M. C., & boyd,  danah. (2018). Situating methods in the magic of Big Data and AI. Communication  Monographs</span>

<span class="censor">That is, *methods* indicate not only the application of computational/statistical methods to social/humanistic/cultural fields, but a also **a contestation of the pertinence of such methods and methodological devices, as well as a reflection on their effects in social research**</span>


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## a. EMBRACE medium/platform-effects

Medium/platforms have their own implicit epistemologies and ontologies (what can be and what how it can be known), thus a methodological approach requires a high degree of criticism and adaptation.

<span class="censor">Not (only) what digital devices *reveal*, but how they produce and perform the social, asking for example, not:</span>

*Which percentage of twitter users believe in x?*

<span class="censor">but</span> 

*How digital practices & objects (of twitter) ground cultural representations/expressions of x?*

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## b. INTEGRATE digital culture and #vernaculars 

<iframe width="948" height="540" src="https://www.youtube.com/embed/TGt1Ukg7q4Y" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>

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## c. COMBINE quant -> qual

* **issue/controversy mapping**: controversy analysis + issue crawling + community detection) with TCAT + gephi

<img src="https://i.imgur.com/3qaZJdy.jpg" width="30%">

<span class="censor">"quantitative curation for qualitative analysis"</span> 
(btw, see this [Friday lecture](https://cc.au.dk/en/news-and-events/events/event/artikel/friday-lecture-double-dating-data-intellectual-cooperation-in-the-league-of-nations/))

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## d. DEAL WITH cross-media


**digital objects use is not equivalent across platforms**

<span class="censor">how does the platform affect the availability of content, and what stories do the content tell, given platform effects?"</span>
<span class="refs">Rogers, R. (2019). Doing Digital Methods. SAGE Publications Ltd.
</span>

This question is even more relevant with the emergence of *alt*-platforms (parler, mastodon, "truth").

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![](https://i.imgur.com/Gpsc9iI.png)

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![](https://i.imgur.com/GPrXpxZ.png)

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# A GOOD EXAMPLE OF <span style="color:hotpink">BAD</span> RESEARCH

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<a href="https://www.nature.com/articles/s41467-020-18566-7#change-history" target="_BLANK"><img src="https://hackmd.io/_uploads/ByAvFP2Uv.png" width="100%"></a>

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<img src="https://i.imgur.com/Nz1iOC8.png" width="70%">

<img src="https://i.imgur.com/YRw6Zjy.png" width="45%">

<span class="refs">Safra, L., Chevallier, C., Grèzes, J., & Baumard, N. (2020). Tracking historical changes in trustworthiness using machine learning analyses of facial cues in paintings</span>

<!--VISUALISATION: DATA IS UGLY 
https://www.reddit.com/r/dataisugly/top/-->

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1. Algorithm (machine learning) to generate trustworthyness ratings (based on facial cues) - (trained on OpenFace **avatars**)
2. Validity tested on natural faces databases of **photography** (originally rated by participants)
3. Not an evaluation directly with participants, to avoid ***bias*** of being influenced by historical cues
4. Check that algorithm is susceptible to the same **biases** as humans (rating "feminine" faces as more trustworthy)
5. Replicates the findings on **google** image searches ("women portraits" vs "male portraits")
6. **RESULT**: trustworthyness increased throughout history ("parallel" to the "rise of liberal values")
7. **RESULT**: trustworthyness increases with afluence (poor people "should" have lower levels of social trust) - (not afluence of individuals, but GDP per capita)


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# RESEARCH QUESTION <span style="color:hotpink">101</span>

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# <span style="color:white;font-size:4em">42</span>

<span style="color:white" class="fragment">The "Answer to the Ultimate Question of Life, the Universe, and Everything"
Calculated over a period of 7.5 million years 
(*The Hitch Hiker’s Guide to the Galaxy*)</span>

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* “O Deep Thought Computer,” he said, “the task we have designed you to perform is this. We want you to tell us...” he paused, “... the Answer!”
* “The answer?” said Deep Thought. “The answer to what?”
* “Life!” urged Fook.
* “The Universe!” said Lunkwill.
* “Everything!” they said in chorus.
* Deep Thought paused for a moment’s reflection.
* “Tricky,” he said finally.  
(...)
* “Forty-two!” yelled Loonquawl. “Is that all you’ve got to show for seven and a half million years’ work?”
* “I checked it very thoroughly,” said the computer, “and that quite definitely is the answer. I think the problem, to be quite honest with you, is that you’ve never actually known what the question is.”  
* “But it was the Great Question! The Ultimate Question of Life, the Universe and Everything!” howled Loonquawl.  
*  “Yes,” said Deep Thought with the air of one who suffers fools gladly, “but what actually is it?”

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Latex ninja: https://latex-ninja.com/2020/03/29/formulating-research-questions-for-using-dh-methods/ 

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# [Final project](https://brightspace.au.dk/d2l/le/lessons/25343/units/677341)


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