Principales desafíos en el campo de la derivación de

Traditionally, archives have been a physical place that foster idea exchanges between

patrons; the movement to online communication makes the establishment of creating an online

space for library patrons a natural transition. Kennedy (2009) noted, “Archives 2.0 must work

alongside, but surely never replace, more traditional strands of research. In working alongside

these traditional strands, it will augment them as a synergy” (p. 9). It is important for archivists to

combine both traditional research methods with new tools provided by social media to meet the

needs of users.

Chern Li, Wellington, Oliver, and Perkins (2015) found that social media is failing in

archives and libraries but can be transformative. The fact that the environment is digital does not

make it any less credible than a tangible written source. Taraborelli, Roth, and Baldassarri (2008)

contend that the unique aspects of social media lie in the structure itself:

Users are not only able to create new social links but also to share content whether in the form of collaborative content productions (such as in wikis or open source communities), content sharing (such as sharing in photo, music or

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video sharing services), content annotation (such as in social bookmarking websites) or content-driven discussion (as in discussion forums or review-based services) (p.1).

It is important to remember that social media is a means of internet communication that enables

social interaction and sharing of media. Interaction within the applications is facilitated by users

establishing their own social networks. When implemented well, the results are tenfold. For

instance, Cianci and Schutt (2014) discussed an archive project that used social media to harness

community outreach after rescuing 10,000 records from a sign painting company. Cianci and

Schutt (2014) noted that if it were not for the incorporation of social media into the project, most

the collection would have remained incomplete.

It is important to recognize that online environments are continuously changing as new

technology becomes available. In order to decide if a social media tool is going to be useful to the

user community, different testing should be employed. Thematic analysis, inferential statistics,

and social network analysis are various ways to work toward a greater understanding of archival

networking.

2.2.3.5 Summary

There are four major aspects to archives and social media: social identity, connection,

collection, and Archives 2.0. Overlap exists between all of the aspects. However, as discussed in

the literature, there are unique points to each that archives should be aware. To begin with, social

identity is much more than just creating a profile. Every action made online adds to one’s social

identity; for instance, ‘Facebook friends’, the action of ‘commenting’ or ‘sharing’ or another post.

In addition, responding to comments or questions made on Facebook also adds to social

identity. These actions provided insight for another Facebook user to understand someone. For an

archive, this might be ‘sharing’ a post made by another archive (an archive that might be in a

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different things: The first being that the archive is trying to connect and be a part of the broader

spectrum of the online world; the second is that it demonstrates to the other archive that there is

an interest in their material. This is part of embracing Archives 2.0.

By embracing Archives 2.0, archives will be able to connect and by connecting, archives

can share users. While it is true that archives have unique collections, interests overlap in wanting

to connect with users and share their story. Instead of archives focusing on their own material, it

would be worthwhile to reach out and ‘share’, ‘comment’, ‘tag’ other entities. Each time that one

of those Facebook interactions takes place, it opens the possibility for different people to know

about the archive and know that that archive exists.

2.3 Thematic analysis

Thematic and content analysis are often used interchangeably in research. At their

foundation, both analyses are a core form of evaluating variations of qualitative research.

However, where content analysis follows a structure of systematic coding across textual

information, thematic analysis emphasizes the recording of patterns as they emerge (Mayring,

2000; Gbrich, 2007; Braun & Clarke, 2006). Thematic analysis involves the search for and

identification of common threads that in the case of social media would extend across an entire

post (De Santis & Ugarriza, 2000). In addition, thematic analysis often refers “to the visual

presentation of themes, codes, and their relationships, involving a detailed account and description

of each theme, their criteria, exemplars and counter examples, and other similar details”

(Vaismoradi, Turunen, & Bondas, 2013, p. 403).

Content analysis is a method heavily used in qualitative research of social media. Content

analysis can also be a quantitative method, however, qualitative research is often used in regards

social media. Qualitative is used to better understand the context of the actions of social media

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make connections. Sullivan et al. (2011) investigated the use of Twitter and the discussion of

medical injuries, such as concussions. Through the content analysis of 1,000 randomly selected

Tweets, Sullivan et al. found that news (33%), sharing personal information/situations (27%), and

inferred management (13%) were the frequently used themes. In a related study, Mishori, Singh,

Levy, and Newport (2014) mapped the flow of tweets of four medical networks on Twitter and

found the collective community to be large and growing with a significant percentage of

individuals who follow more than one group. Mishori et al. suggested that medical groups

develop a more cohesive community of shared users to help users share content.

Politics is a subject that has received a lot of social media research. Himelboim,

McCreery, and Smith (2013) analyzed cross-ideological political views on Twitter using cluster

analysis and found that certain subgroups of highly connected users emerged from buried content

on non-traditional media sites like blogs and social media. In a related study, Naaman, Becker,

and Gravano (2011) analyzed different trends on Twitter; their findings indicate that exogenous

trends were present. Exogenous trends were described by Naaman et al. (2011) to be trends that

had characteristics centered on a certain event, for example, a holiday, a physical event like the

Superbowl or a marathon, and global news events. Many of the approaches to qualitative research

in social media are similar. In the end, the research is aimed at ascertaining more information

regarding a group of people to gauge behavior and interactions that take place in an online setting.

In addition, Adams and McCorkindale (2013) studied Twitter pages from the 2012

presidential candidates and found that the economy, events, and specific primaries were the main

content shared. Overall, the candidates failed to connect and engage in meaningful conversations

amongst users as many of the Tweets were transparent in nature. Adams and McCorkindale point

out an important aspect: social media was created to foster connections and communication

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Holmberg, Bowman, Haustein, and Peters (2014) found that astrophysicists who use Twitter

communicate with a variety of different types of groups in the same platform. Using sentiment

analysis, Holmberg et al. identified information sharing activities between opinion expression and

conversions amongst colleagues all within their ego network.

This study used thematic analysis to evaluate social media. However, given the closely

related nature of content and thematic analysis, content analysis research was also analyzed in

both library and information science and archival science contexts to provide a greater sense of

awareness of the method.