7 Ways NVivo Helps Researchers Handle Social Media Data

Kathleen McNiff is a blogger with QSR International, the people that brought you NVivo. Get in touch with Kath on Twitter @KMcNiff.


Imagine you’re sitting on a qualitative goldmine—in-depth interviews, focus groups, intriguing survey results, nuanced observations and a comprehensive lit review.

 All the traditional boxes are ticked and yet there’s the nagging feeling that something is missing. 

Chances are, it’s social media—and that’s probably why you’re here.

 

The Challenges

There are so many impassioned and revealing conversations taking place online that it’s becoming harder (and more dangerous) to ignore them. 

But embracing social media is not straightforward and you may be grappling with questions such as:

 

• How do I build social media into my research design?
• What platforms are worth concentrating on?
• How should I collect the data?
• What tools and methods should I use to analyse it?

NVivo gives you a practical way to face these challenges.

 

NCapture the web

If you already work with NVivo, you’ll know that it’s a tool for organizing and analyzing qualitative data—but you may not realise that NVivo 10 for Windows comes with a raft of features to support your foray into the brave new world of social media.

 

It all starts with NCapture.

 

This small but powerful plugin sits quietly at the top of your browser (Internet Explorer or Chrome) and lets you capture web pages and social media—and then bring them into NVivo for analysis. It’s a bit like that helpful elephant from Evernote.

You can also capture YouTube videos and conversations from Facebook, Twitter or LinkedIn. This is a boon for researchers who want to facilitate ‘online focus groups’ using these social media platforms—as well as for those who want to get a well-rounded view of their topic by following the latest conversations.

 This brief video (with lovely music) shows you how to gather Twitter data using NCapture:
 

If you use NVivo 10 for Mac—stay tuned, because NCapture is coming soon.

Now, let’s focus on 7 ways NVivo helps you to make sense of your social media data.

 

#1: Gather tweets or posts in a dataset

 

You can search for tweets in your browser and then use NCapture to pull them into a PDF or dataset. The dataset it especially handy because you can filter or sort the content—and use tools to slice and dice the data in different ways.

 

You can do the same for discussions and posts from Facebook or LinkedIn—on these platforms, you can also use the biographical data from user profiles to compare attitudes (men vs women, young vs old—that kind of thing).

 

Sometimes you have to work around the limitations of a particular platform. For example, the number of tweets you can capture is determined by Twitter and can vary depending on the vagaries of Twitter traffic. To follow a particular topic over time, the best approach is to take captures at periodic intervals.

If you want to know more about the inner workings of Twitter—there is a fantastic post right here on NSMNSS blog.

#2: Visualize the most frequently used words

 

You can run a Word Frequency query to see which words contributors are using most often—this can help you get a handle on the themes in your social media data.

 

Visualizing the results in a word cloud may spark insights and reveal connections—they can also liven up a presentation, final paper or blog post.

 

#3: Map the location of tweets or posts

 

You can open a map to see where the action is—and then use this as a launching point for further investigation. For example, you could click on a pin to see the tweets or posts from a particular location.

 

 

#4: Chart users by the number of followers

Shares, likes and follows are the new social currency and they can help to inform your research. If you’re exploring Twitter users - you can create a chart to compare the numbers:

#5: Organize the content into themes

 

You know that qualitative goldmine I mentioned earlier? Well, you can bring the whole thing into NVivo 10 for Windows (including your newly NCaptured social media data) and use ‘coding’ to organize it into themes.

 

For example, whenever you see a reference to ‘education’—whether it be in an interview, article or social media conversation—you can select the content and code it at a ‘node’. Then you can open the node (which is a fancy word for container) and explore all the references to ‘education’ in one place.

 

Coding is a great way to wrangle the chaos of qualitative data—and it’s slightly addictive.

#6: Explore by username or hashtag

 

Do you want to gather tweets from a particular user or hashtag? If your tweets are in a dataset, then ‘auto coding’ is your answer. You can easily roll up the tweets to coding collections by username, by hashtag (what did everyone say about #NSMNSS?), or even by location.

 

Speaking of hashtags - why not start your own twitter chat to gather feedback about an issue or idea?

 

#7: Press the ‘Analyze This’ button

 

Can’t find it?

That’s because, as awesome as NVivo is, it won’t do the analysis for you.

 

Don’t fret because you’ll find plenty of tools for querying the data as well as ways of organizing your own analytical insights (including memos, annotations, models and framework matrices).

Explore the possibilities

Social media has opened a Pandora’s box of opportunities for qualitative research—but you needn’t be overwhelmed because NVivo provides a safe to place to put the box while you explore its contents.

 

Maybe you’re already using NVivo to analyze your social media data?
 

 

Share how you are using NCapture in a short blog post by emailing NSMNSS@natcen.ac.uk

 

 

Introducing the Web Team Our Contributing Expert: Dr. Janet Salmons

Hello to the NSMNSS blogosphere! You may recognize my name from posts and events over the past year, and I am delighted to be a part of the continued work of the New Social Media, New Social Science project as a contributing blogger. I recorded a short introduction for the visual and aural communicators out there!

I have served on the graduate faculty member of the Capella University School of Business and Technology since 1999. I thought I would teach a course or two but fell in love with online teaching and here I am! Capella learners are scholar-practitioners, working adults who integrate life and career experience with rigorous academic study. I currently focus my efforts on dissertation supervision, which provides a living laboratory for observing the development of new research—primarily with online qualitative methods. Their struggles and triumphs help me understand the eclectic mix of practical and scholarly skills needed to successfully conduct research.

I am also an independent researcher, writer and consultant through Vision2Lead. My areas of inquiry include online collaboration and online research methods that allow us to better understand how we interact in the virtual environment. I have an interest in both ethical leadership and ethical research in this connected world.

With Dr. Victoria Boynton I am engaged in an online duoethnography we are calling “Work/Place,” an exploration of the influences of the environment (natural, cultural, physical, virtual) on work creativity and productivity. My recent study on the ways women entrepreneurs use the Internet is the subject of a chapter now in press: “Putting the E in Entrepreneurship: Women Entrepreneurs in the Digital Age” (Salmons, 2014). Online Qualitative Interviews is also in press for a spring release. As well, I edited Cases in Online Interview Research (2012) and wrote Online Interviews in Real Time (2010) for Sage Publications.

Given the above background and interests, my blog posts will include observations and discussion about how and why we use social media for research—and for building community among researchers. I look forward to hearing from you about your questions and dilemmas, thoughts and insights. Comment to my posts, find me at #einterview or www.vision2lead.com.

Reserve your spot now! Final Knowledge Exchange Seminar on 15 March

Dear NSMNSS members,

We're delighted to invite you to the next set of free NSMNSS network activities:

■  We will be holding our final Knowledge Exchange Seminar, hosted at NatCen Social Research on 15 March at 35 Northampton Square, London, EC1V 0AX.

This half day session (12.30-4.30pm) will focus exclusively on the issues related to data and analysis quality arising from social media research, please see the programme copied below for more details. We have very limited spaces for this event so places will be allocated on a first come first served basis and preference will be given to participants willing to contribute a case study or example from their own experience to one of the sessions.  If you would like to attend the seminar please contact us (see below) confirming your contact details (email and phone number). We would hope attendees are able to share their experiences throughout the day of quality issues they have faced using social media.

■  Although the Seminar is free, space is limited; if you do not attend after reserving a place we will make an administrative charge to cover the costs of catering and administration. Please only reserve a space if you intend to attend.

■  In the next couple of weeks we will host the latest in out series of hour long NSMNSS tweetchats related to the issues for discussion in the seminar (follow the hashtag #NSMNSS to participate).

Our Knowledge Exchange Seminars provide an opportunity for researchers, practitioners and policy-makers to share ideas. Each of the four sessions will be interactive, with lots of opportunity for open discussion. We are asking for network volunteers to help deliver the day. You can volunteer to:

■  Tell us about your experiences by providing a descriptive case study– a short 2-3 minute description of an ethical issue or concern that you have encountered in your social media research. Please identify which of the suggested themes in the programme you think your example would fit under and we will ask you to share this during the relevant session, in advance via a blog or on the day with a video blog.

If you would like to contribute to the event on 15^th March please reply to Kelsey Beninger on kelsey.beninger@natcen.ac.uk by 1^st March giving details also of whether and how you would like to contribute. If you would like to contribute a blog or case study, please also include what session your experience relates to.

A live stream of the event will be available, if you are unable to join us please share your thoughts and insights with tweets and comments on our Methodspace forum before and after the event. Remember you can join in network activities here at any time: http://www.natcen.ac.uk/nsmnss/

For a map to NatCen Social Research, please click here.

  

With thanks from the NSMNSS network team.

-------------------------------------------

Blurring the Boundaries - new social media, new social science?

Knowledge Exchange Seminar 4 |
Quality in Social Media Research

15^th March 2013, NatCen Social Research
35 Northampton Square, London, EC1V 0AX

12.30pm	Arrival and lunch
1.00pm	Session 1
	Augmenting curated data with twitter feeds	■     Dr. Luke Sloan, COSMOS, Cardiff University
1.50pm	Session 2
	Practical and epistemological challenges of online research	■     Antonio Casilli, Telecom ParisTech
2.40pm	Break
3.00pm	Session 3
	Depth or disinhibition? What is social media data telling us?	■     Stephen Webster, NatCen Social Research
3.50pm	Session 4
	Draw together key messages for quality	■     Led by NSMNSS
4.30pm	Close and next steps

Qualitative E-Research on E-Entrepreneurs

Not long ago entrepreneurs depended on financial capital to build the physical stores and factories needed to launch a business. And while costly physical operations are still important in some lines of business, 21century entrepreneurs see social capital as essential to a new venture. “Social capital” is the ability to build mutually-beneficial networks of partners, allies and customers (Adler & Kwon, 2002, p. 214; Carolis & Saparito, 2006; OttÓSson & Klyver, 2010; Xiong & Bharadwaj, 2011). Free or cheap technologies make it possible for start-ups to build social capital and sell products and services without huge initial investments. How do women entrepreneurs perceive their opportunities given the availability of these technologies and how do they use them to build networks that generate business? How have their choices vis a vis use of technology influenced the types of businesses they chose to run– and the goals they have for the future? This set of questions drove a study I conducted last year (Salmons, in press), and continued research.

Scholars have studied women entrepreneurs, and online entrepreneurs, but little research has explored the bootstrap, creative, small-scale woman entrepreneur who uses the social web to do her own thing. As well, it was apparent that much of the literature on women entrepreneurs is quantitative—and many studies draw on the same Big Data sources. A prominent one is the Global Entrepreneurship Monitor (GEM) which publishes excellent reports and offers access to dataset downloads. Such data allows us to look at the gap between men and women entrepreneurs, the rate of start-up activity, the growth of women-owned firms, and other topics. Robust as this resource may be, it does not offer exemplars that allow for in-depth exploration of entrepreneurs’ motivations and purpose or to ask why they succeeded (or not), what they hope to achieve and how they feel about it. And the data collected by GEM and others makes little reference to the specific uses of social media and online communications by these entrepreneurs. To probe below the surface, qualitative methods are needed!

Using an exploratory grounded theory and situational analysis approach (Charmaz, 2006; Clarke, 2005), I studied a group of women e-entrepreneurs by following their digital footprints and by interviewing them online. Charmaz points out that in interviews the researcher "starts with the participant's story and fills it out by attempting to locate it within a basic social process" (Charmaz, 2003). Inthis study, participants' stories were located within the social process of business start-up and the entrepreneurial situation. The situational analysis approach allowed me to look closely at the situation by exploring inter-related human (entrepreneur, partners, allies, customers etc) and non-human aspects (technologies) of each entrepreneur’s unique case (Salmons, in press).Social Capital theory (Alfred, 2009; Nahapiet & Ghoshal, 1998) offered a view of the "situation" that focused on the beneficial effects of electronic networks comprised of trusting relationships with partners, online followers or friends, and customers.

Half of my sample included women whom I defined as real-world e-entrepreneurs and half were defined as digital e-entrepreneurs. Real-world e-entrepreneurs use online communications with vendors and customers, partners and allies, and for promotions and advertising. However, products and services are physical and in some cases inherently face-to-face, delivered or purchased on location. Real-world e-entrepreneurs for this study included a jeweler, a designer for an architecture firm and a therapist. Digital e-entrepreneurs similarly use online communications, but are in the business of selling electronic products and services. Electronic products and services online writing, teaching, training, consulting, web design or programming.

Participants created online presence for their businesses using diverse approaches that aligned with business activities. Websites, blogs, wikis and a variety of social media sites allowed for communication, product sales, training, events, networking, advertising, or crowd-source funding. For this study I was not interested in the traffic or the content of a quantity of posts. I was interested in the unique characteristics of each case and through review of participants’ online activities I was able to learn about each respective business, and to generate specific questions for each interview.

Findings for the study include a set of themes which will provide the foundation for the next stage of research. While I gained understanding about ways entrepreneurs can use social media and online communications to build successful businesses from scratch, the study also offered new insights about the ways researchers can use online tools at every stage of the study. I used social media (Twitter, Linked In, Facebook, Kickstarter) to recruit participants by posting a link to a description of the study posted on my own website. I used Survey Monkey to create an electronic consent form (see discussion of this approach and example). Interviews were conducted online in Adobe Connect, using text, verbal and visual modes of communication. While the resulting chapter will appear in a book, I have used excerpts in various posts and presentations to disseminate some of the findings. One reflection is that online interview research concerns more than the interview, that online qualitative research is inherently multi-modal involving inter-related and overlapping participant and outsider observations, document and records analyses. Now I want to build an intentionally multi-modal approach into next phase of the study—stay tuned!

Janet Salmons, PhD

References

Adler, P. S., & Kwon, S. W. (2002). Social capital: Prospects for a new concept.

Academy of Management Review, 27, 17-40.

Alfred, M. V. (2009). Social capital theory: Implications for women's networking

and learning. New Directions for Adult & Continuing Education(122), 3-12. doi:

10.1002/ace.329

Carolis, D. M. D., & Saparito, P. (2006). Social capital, cognition, and

entrepreneurial opportunities: A theoretical framework. Entrepreneurship: Theory &

Practice, 30(1), 41-56. doi: 10.1111/j.1540-6520.2006.00109.x

Charmaz, K. (2006). Constructed grounded theory: A practical guide through

qualitative analysis. Thousand Oaks: Sage Publications.

Clarke, A. (2005). Situational analysis: Grounded theory after the postmodern

turn. Thousand Oaks: Sage Publications.

Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and the

organizational advantage. Academy of Management Review, 23(2), 242-266.

OttÓSson, H., & Klyver, K. I. M. (2010). The effect of human capital on social

capital among entrepreneurs. Journal of Enterprising Culture, 18(4), 399-417.

Salmons, J. E. (in press). Putting the “E” in entrepreneurship: Women entrepreneurs in

the digital age. In L. Kelley (Ed.), Women Entrepreneurship: New Management

and Leadership Models. Westport: Praeger.



Challenges and opportunities of Twitter as a corpus

In the run up to our next Knowledge Exchange Event we'll be posting a series of blogs on new social media and qualitative research methods. The first is by Amy Aisha Brown, a research student in the Faculty of Education and Language Studies at the Open University. 

I won’t deny it, I am another one of those researchers who has been wowed by the idea of using social media in research, but I’d argue that it hasn’t been without good reason. I am interested in the ideologies of the English language in Japan, and I am looking to find out how these ideologies pan out in everyday discussions. The hope is that a wide scale investigation will complement research in the area that takes a more ethnographic approach (see Philip Seargeant’s work). So, what really pulled me into the idea of using social media, and Twitter specifically, were the possibilities for accessing a large body of relevant, naturally occurring discourse on everyday topics.

A quick search for “英語” (Japanese for ‘English’, as in the language rather than the people or the muffins) brings up new tweets every few seconds. While this shows just how much potential data is out there, ways of getting hold of tweets and getting them into a format that I can work with for the corpus analysis element of my study, are not as easy to find.

NVivo 10 and the associated browser plugin NCapture are two of-the-shelf tools I have used so far. NCapture lets you use Twitter’s simple search feature to find relevant tweets, and once you import the search results into NVivo, they appear alongside their metadata as a searchable data set that is ready for qualitative coding. This has been a useful way of getting an initial idea about what I can expect to get from tweets, but NVivo is unlikely to be a long-term solution for collect and corpus analysis for two reasons:

      1. Collecting tweets 

• Using Twitter’s basic search function only gives access to a selection of the public tweets produced, a selection that is “optimized to serve relevant tweets to end-users” rather than a random sample or a sample based on any published definition. 
• This way of collecting tweets also only allows you to collect around 1500 at a time, making it difficult (or at least very time consuming) to collect most of the relevant tweets accessible through the search function. 

      2. Corpus tools 

• NVivo has lots of nice tools for visualizing text, such as word frequency lists and tag clouds but neither is it a tool built for corpus analysis nor one that is optimised for Japanese text. 
• NCapture does not capture tweets in a way that makes them easily processed by software other than NVivo. 

In many ways, these are not just the limitations of the NVivio/NCapture combo, they are the technical challenges of my research in general. It might be that I have to compromise on what I hope to achieve, but for the time being I am enjoying looking into other options. If you have any suggestions, I'd be happy to hear. Otherwise, I’ll be getting back to it …