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# Approaches to Digital Methods

<br>

## <span class="censor">Engaging with Digital Methods - Communicating Research</span>

### Graduate School, Arts at Aarhus University

<br>

Pablo Velasco // Information Studies <br> Aarhus University // [pablov.me](https://pablov.me)

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# Social research
* # \+ web
* # \+ data
# Virtual Methods
# Digital Methods

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# Sociometrics
* Moreno (1934)
* Discover social life through network properties & topologies
* Analysis of relational data
* Gain insight into social relations and make them available to intervention (Guggenheim 2012) -> participants become observers of their own problems

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<img src="https://gitlab.com/xpablov/data-studies/-/raw/master/DS19/S07/moreno-rooms-girls.png" width="45%">
<img src="https://gitlab.com/xpablov/data-studies/-/raw/master/DS19/S07/moreno-topological-girls.png" width="40%"><br>
<small>Likes and dislikes in a girl's boarding school (Moreno 1934 in Gießmann 2017)</small>

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# Social research + web (big) data

* Digital technologies enable new practices for recording, analyzing, and visualizing social life (Fielding 2008).

<img src="https://socialmedia.qut.edu.au/wp-content/uploads/2015/08/Blue-graph.png" width="100%">

* Optimistic (Latour 2012) and Pesimistic approaches (Savage and Burrows 2007)

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### (social) Big Data

* boyd and Crawford (2012)
* not size, but scrutability
* representations (e.g. nodes and graphs) not necessarily convey relationships between people
> less about data that is big than it is about a capacity to search, aggregate, and cross-reference large data sets

* Uprichard (2013):
* (mostly) social data
* social systems are not well modelled or known through universal laws
* techiques based on normalisation (ignoring the outliers)
* looking at social data, doesn't mean that what they [data scientist] are doing is social

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**Redistribution (Marres 2012)**
* redistribution of research: not so much an opposition between IT firms and researchers (Savage and Burrows 2007), but a reconfiguration of agents in social research

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**Reassembling (Ruppert et al 2013)**
* Not what digital devices *reveal*, but how they produce and perform the social
* Devices as both:
* the *materials* of social life: liveliness of data
* the *apparatuses* to know it: material, institutional, and behavioural elements

apparatus/assemblage/dispositif
<span class="censor">"a thoroughly heterogeneous ensemble consisting of discourses, institutions, architectural forms, regulatory decisions, laws, administrative measures, scientific statements, philosophical, moral and philanthropic propositions – in short, the said as much as the unsaid." (Foucault 1980)</span>

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9 propositions for reassembling social science methods (Ruppert et al 2013):

1. **Transactional actors**: circulation with non-individuals / users as by-product
2. **Hetereogenity**: post-demographics / non-human association
3. **Visualisation**: as tool for legitimising
4. **Continuous time**: on-going dynamics
5. **'Whole' populations**: but not tied to geodemographics
6. **Granularity**: e.g. highly specific databases
7. **Expertise**: not crucial / new mediators
8. **Mobile**: active / boundary-less
9. **Non-coherence**: distributed knowledge / 'democratization' and/or erosion of older forms of validation

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# Virtual Methods

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### "Digital Methods" (big umbrella)

* Digital methods: “the use of online and digital technologies to collect and analyse research data (Snee et al 2016)
* Snee et al include:
* web-based surveys (Dillman 2007)
* online interviewing and focus groups (Kazmer and Xie 2008)
* computer mediated discourse-analysis (Herring 2004)
* digital ethnographies e.g. virtual ethnography (HIne 2000)

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## Virtual ethnography (web 1.0)

- text as main form of communication
- multi-sited ethnography (Marcus 1995)

Hine (2009)
- people producing websites
- participants in online discussions

Hine methods:
- document analysis on websites or media coverage
- discourse analysis
- participation in online events
- interviews

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* ~~5~~ **4 views** (along a spectrum) (Marres, 2012):
* **methods as usual**: old social methodologies incorporated into digital devices
* **big-methods**: vast datasets allow us to perform large-scale analysis on *real* network dynamics
* **virtual methods**: adaptation of the social research methods into the digital
* **digital methods**: adapt digital devices for the purposes of social research

* digital: a) tools, b) social data, c) platforms

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# Digital Methods

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**Digital methods** is a term coined as a counterpoint to virtual methods, which typically digitize existing methods and port them onto the Web. Digital methods, contrariwise, **seek to learn from the methods built into the dominant devices online, and repurpose them for social and cultural research**. That is, the challenge is to study both the info-web as well as the social web with the tools that organize them. There is a general protocol to digital methods. At the outset stock is taken of the **natively digital objects that are available (links, tags, threads, etc.) and how devices such as search engines make use of them**. Can the device techniques be repurposed, for example by remixing the digital objects they take as inputs? Once findings are made with online data, where to ground them? Is the baseline still the offline, or are findings to be grounded in more online data?<br><br><small>(https://wiki.digitalmethods.net/Dmi/WinterSchool2021)</small>

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#### "Natively digital" methods & objects
<span class="censor">The rise of the Internet enables new research methods that deploy specifically digital devices such as links, comments and shares (Rogers 2009; Rogers 2013)</span>

* **methods** embedded in online devices: of crawling, scraping, folksonomy
* digital **objects**: tweet, username, timestamp, hyperlink, hashtag
* built upon existing services

#### Spheres (Rogers 2013)

1. mid to late 90s: hyperlink, individual website analysis
2. early to mid 00s: blogosphere, search engine critique
3. late 00s: location-aware, web 2.0, social media

**"cross-spherical analysis”: web, blogs, news, twitter, etc**

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* **networks**
* ANT ontology (Latour 2012)
* network analysis (Venturini et al 2015)
* **platforms**
* platform effects (Malik 2016)
* platformisation of the web (Helmond 2015)
* **hashtags**
* ad-hoc publics (2011)
* **controversies/issues**
* controversy/issue mapping (mappingcontroversies.net / issuemapping.net)

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<img src="https://hackmd.io/_uploads/H1yfkOnLw.jpg" width="100%">

<small>Himba tribe color recognition experiment / Namibia
(Robertson, Davidoff, Davies, and Shapiro 2006)</small>

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# Bias

* *the* digital (relational and interpretative and device-aware, instead of representational)

>bias does not just involve a negative, distorting influence of the research apparatus on the ‘social phenomenon’ under investigation; rather **the very constitution of digital data involves dynamics that are at once social and technical, their ‘content’ is a consequence both of how digital technologies work and what people do with them**, in ways that are difficult to dis-entangle (Marres 2017)

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* There are, then, two different ways to treat the methodological problem of bias in digital social research: **the precautionary approach treats digital media technologies as a source of noise or corruption that must be neutralized**, while the affirmative approach treats digital devices as an empirical resource for social enquiry. The former proposes that digital content must be dis-embedded from online settings in order to secure the validity of our analysis (Guido and Venturini, 2012). T**he latter seeks to bring publicity devices that are specific to digital culture within the empirical frame of social and cultural research** (Rogers, 2009; Marres, 2012a) (...) For the affirmative approach, digital devices are in part formative and therefore potentially indicative of substantive dynamics of social, political and public life: they organize sources in ways that bring relevant socio-technical formations to the fore (Gillespie, 2010)

(Marres 2017)

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