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Qualitative and Mixed Methods Social Media Research: A Review of the Literature

Qualitative and Mixed Methods Social Media Research: A Review of the Literature

Qualitative and Mixed Methods Social Media Research: A Review of the Literature

Chareen L. Snelson 1

Abstract Social media technologies have attracted substantial attention among many types of users including researchers who have published studies for several years. This article presents an overview of trends in qualitative and mixed methods social media research literature published from 2007 through 2013. A collection of 229 qualitative studies were identified through a systematic literature review process. A subset of 55 of these articles report studies involving a combination of qualitative and quantitative methods. Articles were reviewed, analyzed, and coded through a qualitative content analysis approach. Overall trends are presented with respect to the entire collection of articles followed by an analysis of mixed methods research approaches identified in the subset of 55 studies. The most commonly used research approaches involved collecting data from people through interview, focus group, and survey methodologies. Content analysis was the second most commonly used approach whereby researchers use Facebook posts, Tweets (Twitter posts), YouTube videos, or other social media content as a data source. Many of the studies involving combinations of quantitative and qualitative data followed a design resembling Creswell and Plano Clark’s basic mixed methods typology (e.g., convergent parallel, explanatory sequential, and exploratory sequential).

Keywords social media research, Web 2.0, Facebook, Twitter, YouTube, mixed methods, qualitative

This article presents a descriptive methodological analysis of

qualitative and mixed methods approaches for social media

research. It is based on a systematic review of 229 qualitative

or mixed methods research articles published from 2007

through 2013 where social media played a central role. Publi-

cation trends are presented for the entire set of articles followed

by analysis of a subset of 55 studies that combined qualitative

and quantitative approaches consistent with an established

mixed methods typology (Creswell, 2014; Creswell & Plano

Clark, 2011). The literature analysis is first contextualized by

presenting a brief overview of related scholarly activity in the

emerging field of social media research. This is followed by a

discussion of publication trends and methodologies applied in

this systematic literature review.

Kaplan and Haenlein (2010) defined social media as ‘‘ . . . a group of Internet-based applications that build on the ideolo-

gical and technological foundations of Web 2.0, and that allow

the creation and exchange of User Generated Content’’ (p. 61).

The emergence of social media technologies has been

embraced by a growing number of users who post text mes-

sages, pictures, and videos online (Duggan, 2013; Duggan,

Ellison, Lampe, Lenhart, & Madden, 2015). Reports of world-

wide social networking activity suggest that there were 1.96

billion users in 2015 with predictions of 2.44 billion users by

2018 (Statista, 2015). Of all the social networking sites, Face-

book, Twitter, and YouTube are among the most popular rank-

ing within the top 10 of a list of most heavily visited sites on the

web (Alexa, 2015). The combination of prolific user activity

and production of user-generated content has captured the

attention of scholars and researchers who seek to understand

social media and its role in contemporary society.

Considerable attention has been given to social media

research as evidenced by the expanding literature base and

growing number of comprehensive literature reviews, which

have been conducted to explore various facets of social media

research and scholarship. A matrix summary of 20 social media

literature reviews published from 2011 through early 2014 is

provided in Table 1. Although not a comprehensive list, each of

1 Department of Educational Technology, Boise State University, Boise, ID,

USA

Corresponding Author:

Chareen L. Snelson, Department of Educational Technology, Boise State

University, Boise, ID 83725, USA.

Email: [email protected]

International Journal of Qualitative Methods January-December 2016: 1–15 ª The Author(s) 2016 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1609406915624574 ijqm.sagepub.com

Creative Commons CC-BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 3.0 License (http://www.creativecommons.org/licenses/by-nc/3.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).

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the articles in Table 1 represents a systematic literature review

with the methodology for sampling and analysis clearly

described by the author(s). The range of topics covered across

the collection of literature review works reveals some of the

diversity in emphasis and fields of study from which the works

emerge. Some authors have focused on categorization of trends

in academic literature related to specific social media platforms

such as Facebook (B?achnio, Przepio?rka, & Rudnicka, 2013;

Caers et al., 2013; Hew, 2011; Manca & Ranieri, 2013; Nad-

karni & Hofmann, 2012; Wilson, Gosling, & Graham, 2012),

Twitter (Dhir, Buragga, & Boreqqah, 2013; Williams, Terras,

& Warwick, 2013), or YouTube (Snelson, 2011). Other studies

are grounded within a particular subject or field of study to

examine social media as it relates to topics such as adolescent

well-being (Best, Manktelow, & Taylor, 2014), health-care

professionals (Hamm et al., 2013), type 1 diabetes (Jones, Sin-

clair, Holt, & Barnard, 2013), tourism and hospitality (Leung,

Law, van Hoof, & Buhalis, 2013), or prediction of real-world

events (Kalampokis, Tambouris, & Tarabanis, 2013).

The prior literature reviews listed in Table 1 indicate that

much has already been covered on the subject of trends in

social media literature. Yet, there is little information about

trends in qualitative and mixed methods approaches to social

media research. Prior literature reviews have included discus-

sions of trends in research approaches but have provided a

more global classification of general trends (e.g., Best et al.,

Table 1. Systematic Literature Reviews on Social Media Topics.

Author(s) Emphasis of Review Field(s) of Studya Articles/Papers Reviewed

Best, Manktelow, and Taylor (2014)

Research on the effects of social networking on adolescent well-being

Sociology, social work, and social studies

43

B?achnio, Przepio?rka, and Rudnicka (2013)

Research focusing on the role of psychological traits in explaining Facebook use

Psychology 59

Caers et al. (2013) Peer-reviewed articles and papers on Facebook published between 2006 and 2012 that focus on personality of users

Psychology and economics

114

Dhir, Buragga, and Boreqqah (2013)

Empirical, conceptual, and theoretical studies on Twitter and its use in education

Education 43

Gholami-Kordkheili, Wild, and Strech (2013)

Research, commentaries, editorials, and opinion papers on medical professionalism and social media

Health care and medical 108

Hamm et al. (2013) Research on social media use by health-care professionals or trainees published between 2000 and 2012

Health care and medical 96

Hew (2011) Research focusing on the use of Facebook by students and teachers

Education 36

Jones, Sinclair, Holt, and Barnard (2013)

Research on the use of social networking to discuss the risks of Type 1 diabetes mellitus

Health care and medical 6

Kalampokis, Tambouris, and Tarabanis (2013)

Research where social media data were used to predict real- world phenomena

Information systems 52

Khan (2012) Research on social media systems published 2003 to 2011 Information systems 274 Khang, Ki, and Ye (2012) Social media research trends in four disciplines (advertising,

communication, marketing, and public relations) published 1997–2010

Advertising, communication, marketing, and public relations

436

Leung, Law, van Hoof, and Buhalis (2013)

Social media–related research articles in tourism and hospitality published between 2007 and 2010

Tourism and hospitality 44

Manca and Ranieri (2013) Research with a focus on Facebook as a learning environment

Education 23

Nadkarni and Hofmann (2012)

Research on the psychological factors contributing to Facebook use

Psychology 42

Park and Calamaro (2013) Studies where social network sites are used for recruitment, intervention, or measurement in health research of adolescents and young adults

Health care, medical, and nursing

17

Snelson (2011) Trends in academic literature about YouTube published between 2006 and 2009

Interdisciplinary 188

Van Osch and Coursaris (2014)

Social media research productivity based on journal articles and conference proceedings from October 2004 to 2011

Interdisciplinary 610

Williams, Terras, and Warwick (2013)

Twitter and microblogging research published from 2007 to 2011

Interdisciplinary 575

Wilson, Gosling, and Graham (2012)

Trends in research on Facebook Social science 412

Zhang and Leung (2014) Social networking research published in six high-ranking communication journals from 2006 to 2011

Communication 84

a Information in the Field(s) of Study column is based primarily on statement of purpose and content focus of each literature review article.

2 International Journal of Qualitative Methods

2014; Hamm et al., 2013; Jones et al., 2013; Williams et al.,

2013). This literature review serves to expand the knowledge

base regarding how qualitative and mixed methods have been

applied to social media research. There are several reasons why

this might be important. Social media research is a relatively new

field of study that has emerged in conjunction with the develop-

ment of social media technologies and the upsurge in their use

(Duggan et al., 2015). Little is known about how many qualitative

and mixed methods social media studies have been published,

where they originate, or which academic journals publish them.

Furthermore, trends in the selection of research design, data col-

lection techniques, and analytic approaches are not well known.

The potential value of examining trends in the use of qua-

litative research approaches (e.g., interview, focus group, and

qualitative content analysis) lies in uncovering how researchers

design studies to gain insights into how and why people engage

with social media as well as the meaning that is attached to

experiences with social media. For example, Fox, Warber, and

Makstaller (2013) collected data from mixed-sex focus groups

to help them answer questions about the role of Facebook in

romantic relationship development. In another study, Greene,

Choudhry, Kilabuk, and Shrank (2011) conducted a qualitative

evaluation of posts from Facebook communities dedicated to

diabetes to reveal how patients, family members, and friends

share information and receive emotional support.

Mixed methods research approaches ‘‘in which the

researcher gathers both quantitative (closed-ended) and quali-

tative (open-ended) data, integrates the two and then draws

interpretations based on the combined strengths of both sets

of data to understand research problems’’ (Creswell, 2014,

p. 2) also have potential value in social media research. For

example, Morgan, Snelson, and Elison-Bowers (2010) used qua-

litative analysis of social media content together with a survey to

uncover patterns of behavior and attitudes regarding depictions

of alcohol and marijuana use by young adults on social media

websites. As another example, Vyas, Landry, Schnider, Rojas,

and Wood (2012) combined a survey with follow-up interviews

to examine short message services and social media use among

Latino youth and the potential role of these services as methods

of communication in public health programs. These examples

illustrate the potential of qualitative and mixed methods research

approaches to uncover new insights through the complimentary

combination of methods. Yet, the question of how researchers

have been applying these approaches in social media studies has

not been explored in depth.

What this literature review contributes is a summary of

general trends in qualitative research studies together with a

more in-depth analysis of mixed methods approaches for social

media research. The overarching research questions guiding

this systematic literature review study were:

? What are the overall trends in qualitative and mixed methods social media research?

? To what extent does the design of mixed methods social media studies align to an established typology for mixed

methods research?

Method

The central aim of this literature review was to identify trends

in qualitative and mixed methods approaches used in the emer-

gent field of social media research. The review is descriptive

and follows an integrative synthesis approach, which ‘‘attempts

to summarize the contents of multiple studies and minimizes

any interpretation on the part of the reviewer’’ (Harden &

Thomas, 2010, p. 752). The unit of analysis was a peer-

reviewed journal article reporting the results of a qualitative

or mixed methods research study where social media played a

central role. The scope of the literature review was limited to

articles published from 2007 through 2013. The reason for the

initial cutoff was that literature in the years before 2007 was

scant, given that social media is a relatively new phenomenon.

According to company websites, Facebook was invented in

2004 (Facebook, 2015), YouTube in 2005 (YouTube, 2015),

and Twitter in 2006 (Twitter, 2015). A previous literature

review on YouTube scholarship indicated that publications

began to appear in 2006, but no research studies were published

prior to 2007 (Snelson, 2011). Williams, Terras, and Warwick

(2013) selected 2007 as a starting point for their literature

review of Twitter and microblogging research because that is

when the first papers began to appear. Facebook research was

published as early as 2005 (Wilson et al., 2012) but seems to

have started building momentum in 2007. Therefore, the deci-

sion was made to set the initial cutoff at 2007 with a final cutoff

of 2013, which was the last full year before the review was

conducted in 2014.

Peer-reviewed journal articles were selected and analyzed

through a systematic process consistent with the prior litera-

ture review studies listed in Table 1. Selection and analysis of

articles proceeded through a series of the four stages illu-

strated in Figure 1.

Stage 1: Presearch

During the presearch phase, key words and databases were

selected based on a combination of (a) strategies used in prior

literature reviews and (b) test searches with candidate key

words, filters, and databases. Some of the prior literature

reviews focused on specific social media platforms (e.g., Face-

book, Twitter, and YouTube), whereas others investigated cer-

tain aspects of social media usage or content regardless of

platform. The present study integrates a combination of both

platform-specific and general search phrases to explore an

array of studies involving single or multiple types of social

media. The key words used were Facebook, Twitter, YouTube,

social media, and social networking. Each of these search

phrases has been used in at least one prior literature review.

Many of the prior social media literature reviews were

grounded in a particular field of study. Searches were con-

ducted in combinations of databases, which sometimes

included databases indexing literature specific to the field

(e.g., PubMed for medical-related literature reviews). The

present literature review is interdisciplinary with a focus on

Snelson 3

trends in research methodology regardless of discipline.

Therefore, searches were conducted exclusively in the fol-

lowing multidisciplinary databases, which have all been used

in prior literature reviews: Academic Search Premier, Web of

Science, and Google Scholar. Together, they offer substantial

and complementary access to the academic literature from

multiple disciplines.

Stage 2: Search

The search was conducted in January 2014 for articles pub-

lished from 2007 through 2013 that had bibliographic entries

available in the selected databases. The specific strategy for

searching each of the databases (Academic Search Premier,

Web of Science, and Google Scholar) is outlined here in detail

to make them replicable for other researchers.

Academic Search Premier and Web of Science involved a

key word search conducted in a similar manner. Each of the

search phrases, YouTube, Facebook, Twitter, ‘‘social media,’’

and ‘‘social networking,’’ were entered one at a time in a series

of searches. Filers were applied with each round of searches to

retrieve peer-reviewed articles where the search phrase was

contained in the title. For example, the search for Facebook

articles was set to retrieve peer-reviewed articles with Face-

book in the title. Search results were exported directly from

each database in batches to the online version of EndNote

(Thompson Reuters, 2014a). At the time of searching, Aca-

demic Search Premier permitted export of 100 citations per

batch and Web of Science permitted export of 500 citations

per batch. All citations from each round of searches were

exported in batches until all of the results were copied into

EndNote online.

Google Scholar was included as one of the databases

searched for during this literature review due to its broad reach

across interdisciplinary academic scholarship indexed on the

Internet and its use in prior literature review studies (see

B?achnio et al., 2013; Dhir et al., 2013; Kalampokis et al.,

2013; Williams et al., 2013; Wilson et al., 2012). Unfortu-

nately, Google Scholar has certain limitations. Williams et al.

(2013) searched Google Scholar for their literature review of

academic work related to Twitter but acknowledged the lack of

control over search fields and results containing many works

unrelated to the purpose of their research. An additional issue is

the sheer volume of results that might appear in a Google

Scholar search. Researchers might not have the time or

resources to sort through thousands of results to find articles

matching inclusion criteria for articles. Furthermore, Google

limits access to the first 1,000 search results (see Google,

2015), thereby making it impossible to access all of the results.

This limitation can be verified by clicking through to the last

page of a large set of search results.

The limitations with Google Scholar necessitated a modified

search strategy to obtain a manageable set of results that

yielded relevant articles not found through searches of Aca-

demic Search Premier and Web of Science. The lack of control

over search fields acknowledged by Williams et al. (2013) was

addressed by appending additional key words to restrict results

to relevant articles. As previously explained, the unit of anal-

ysis was a peer-reviewed journal article reporting the results of

a qualitative or mixed methods research study where social

media played a central role. Therefore, the search phrases were

adjusted to target both the type of social media and the type of

design in each round of searches. For example, the search for

Facebook literature was conducted in two rounds, with the

search phrase Facebook qualitative used in the first round fol-

lowed by Facebook mixed method in the second round. A sim-

ilar approach was used to search for literature on Twitter,

YouTube, social media, and social networking articles. This

targeted search produced a manageable results list but pro-

duced only eight relevant articles that were not already found

in the Academic Search Premier and Web of Science databases.

Google Scholar ultimately served as an ancillary search tool

that produced a few additional articles, but, in this particular

case, it created the problematic decision of whether to choose

(a) too many results that were labor-intensive to review and

could not be fully accessed or (b) a restrictive search that might

have limited the results to a narrower scope than desired. The

restrictive search option, although not ideal, was selected due

to its feasibility. Other researchers are encouraged to consider

the limitations of Google Scholar prior to using it to obtain

literature for a systematic review.

The process of removing duplicate citations was conducted

after the searches were complete and citations had been

imported into the online version of EndNote (Thompson Reu-

ters, 2014a). First, the duplicate removal tool was used to iden-

tify as many duplicates as possible that had been imported from

the different databases. This was followed by manual inspec-

tion of the citations to remove additional duplicates that had not

been entered into the databases in the same way. For example,

the author name or title might have been entered differently in

one database as compared to the others. The citations were

Figure 1. Stages in the literature review process.

4 International Journal of Qualitative Methods

combined into a single group (minus duplicates), leaving a total

of 3,322 unique article citations.

Stage 3: Data Cleaning

Abstracts and full-text copies of the articles were reviewed to

determine eligibility for analysis. Articles were selected if they

met the following criteria: (a) the study applied qualitative

research methodology or mixed methods research with a qua-

litative research component, (b) the study emphasized online

social media, (c) the article was published in a peer-reviewed

journal, and (d) a full-text English copy of the article was

available. A total of 229 studies met the criteria with a subset

of 55 of these studies involving both qualitative and quantita-

tive (i.e., mixed) methods.

Stage 4: Analysis

A qualitative content analysis methodology, based on Schre-

ier’s (2012) approach, was used to structure the review and

analysis of the literature. Qualitative content analysis is a

descriptive research method involving development of a cod-

ing frame and qualitative coding of data. The coding frame was

both concept driven (defined in advance) and data driven

(derived from data during coding) as described by Schreier.

Essentially, the concept-driven part of the coding frame was

designed to classify studies according to research design (qua-

litative and mixed methods) and social media emphasized in

the research. The data-driven portion of the coding frame came

primarily from tagging and coding articles based on research

approaches used in the study, as will be discussed momentarily.

A single researcher conducted the present study; therefore, a

multiphase approach was taken to review the content at differ-

ent points in time and to cross-check results for consistency.

The articles had all been reviewed for eligibility for the study

during the data-cleaning stage, but the actual analysis of con-

tent began with a round of review and tagging using the Men-

deley’s (2014) reference management software. Full-text

copies of the articles were obtained and imported into Mende-

ley where they were reviewed, bibliographic information was

verified, and tags were applied to each article to indicate type

of social media emphasized and research approaches used in

the studies. The tagging process served as a first round of

classification and coding.

To conduct the second round of coding, bibliographic infor-

mation first was exported from Mendeley in the Research

Information Systems file format. This text file was imported

into the NVivo (Version 10) qualitative analysis software pro-

gram (QSR International, 2014). This process accomplished

two goals: (a) it imported full-text copies of the articles into

NVivo and (b) it simultaneously created an internal classifica-

tion sheet (similar to a spreadsheet), which contained biblio-

graphic information that was linked to each imported article.

The classification sheet was created for the purpose of running

queries within NVivo and for export to Excel (Microsoft, 2014)

where further analysis of overall trends could be conducted.

Additional attributes (similar to spreadsheet columns) were

added to the classification sheet so that each article could be

categorized based on the social media emphasized in the study.

The labeled categories comprised ‘‘Facebook,’’ ‘‘Twitter,’’ or

‘‘YouTube’’ for studies that focused on those specific social

media platforms alone. A ‘‘Combination’’ category was used to

label studies involving more than one type of social media that

included Facebook, Twitter, YouTube, or some combination of

these platforms. A category for ‘‘Other Social Media’’ was

used to label studies involving other named social media plat-

forms such as MySpace. An ‘‘Unspecified’’ category was used

for studies that emphasized more general social media topics

where there was no specific mention of any particular social

media platform.

In addition to the categorization within the classification

sheet, each entire article was coded as a case node in NVivo

based on author names to facilitate the process of running

matrix queries of authors versus content. Next, content within

each article was coded based on the research approach applied

to conduct the social media study. A set of top-level nodes, set

at the highest point of a hierarchical node structure, was created

prior to analysis to serve as the concept-driven coding frame, as

discussed earlier. Nodes were created for qualitative and mixed

methods research studies. In addition, child nodes were created

under the mixed methods node for each of the mixed methods

research design types described by Creswell and Plano Clark

(2011). Nodes for specific approaches such as interviews, focus

groups, surveys, or content analysis were generated later when

they were identified during analysis and coding of the individ-

ual articles. Research approaches had already been tagged on

the articles in Mendeley during the first round of review, so the

NVivo coding was cross-checked with the Mendeley tags to

verify consistency. When discrepancies were observed, articles

were reviewed again to resolve these differences.

Trends across the set of tagged and coded literature were

identified through analysis of coded article text, matrix

queries of articles and codes, and information in the article

classification sheet. The classification sheet was exported

from NVivo as a spreadsheet for analysis in Excel where pivot

tables were created to generate charts and frequencies of pub-

lication trends.

Limitations and Delimitations

Prior literature reviews of social media research have described

limitations that are equally applicable to the current study.

Factors attributed to scope restrictions based on specific social

media platform, databases, types of literature (e.g., articles and

conference papers), languages, publications (e.g., specific jour-

nals), or use of specific search phrases have been discussed

(e.g., B?achnio et al., 2013; Gholami-Kordkheili, Wild, &

Strech, 2013; Khan, 2012; Khang, Ki, & Ye, 2012; Leung

et al., 2013; Williams et al., 2013; Wilson et al., 2012; Zhang

& Leung, 2014). Restricting the scope of a literature review can

be beneficial in making the study feasible and focused. How-

ever, it also means that some literature will most likely be left

Snelson 5

out of the analysis. The same issue holds true for the present

study with its own restrictions on language, publication type,

databases, and search phrases. The restrictions and criteria for

inclusion should be communicated in literature reviews, as they

are here, to ensure that other researchers are made aware of

limitations impacting coverage. Furthermore, these details per-

mit replication or comparison among literature review studies.

The restrictions and selection criteria have been provided in the

method section earlier to ensure that these details are available

for interested researchers. In addition, a complete bibliography

of all of the studies included in this review, including a cate-

gorized list of mixed methods studies identified by the author,

is available online at https://sites.google.com/site/qualmix/

bibliography.

Strategies for describing, defining, or classifying mixed

methods research studies have been proposed through the

development of various typologies, models, or frameworks

(Creswell, 2014; Creswell & Plano Clark, 2011; Guest, 2012;

Johnson & Onwuegbuzie, 2004; Nastasi, Hitchcock, & Brown,

2010). The present literature review limits discussion to the

typology developed by Creswell and Plano Clark (2011). This

typology served as a useful tool for organizing and describing

timing and priority of data collection and analysis within social

media research.

Results and Discussion

The results of this systematic literature review study are orga-

nized in a general-to-specific manner. These …

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