Things that keep me awake at night: ethical considerations when researching fan communities online

Milena Popova is a PhD researcher at the Digital Cultures Research Centre, UWE Bristol. She is researching approaches to sexual consent in fanfiction and online fan communities. She tweets as @elmyra and blogs about her research at pornresearcher.eu.

My PhD research focuses on depictions of sexual consent in online fanfiction: amateur-produced fiction based on existing media, such as TV shows, movies or books. I am using a range of methods to study the fanfiction community and its cultural output. Here some thoughts on the ethical questions I have come up against while designing and conducting my research.

A brief introduction to the fanfiction community:

Modern fanfiction originated in paper zines, but these days the vast majority of the community (or communities, really) live and communicate online, in spaces that are on the cusp of the private-public boundary. Fanfiction, and the communities that produce it, are a Google search away - if you know about them.

The fanfiction community consists predominantly of women and non-binary people, a majority of whom identify as members of a sexual, gender or romantic minority (lesbian, gay, bisexual, transgender, non-binary, asexual, aromantic, etc.). Statistically, a significant proportion of community members are survivors of sexual or gender-based violence. (In the UK, 45% of women have experienced rape, sexual assault, domestic abuse or stalking. It is reasonable to assume that this is reflected in the make-up of the fanfiction community.) These demographics are reflected in the kinds of stories the community produces: stories which focus on (often queer) sexual and romantic relationships, sexually explicit stories, stories which explore issues of sexual consent extensively and in profoundly nuanced ways - which is the focus of my research.

In many ways, the fanfiction community is vulnerable, though not necessarily in a way you would find as a tickbox on an ethics form. The social stigma attached to marginalised sexualities (including women’s and queer sexualities) means that there are potentially significant social and economic consequences associated with being identified as a reader or writer of erotic fanfiction. Additionally, fanfiction is generally based on copyrighted material (or sometimes real people such as actors, musicians and other celebrities), and there are also legal risks involved in producing and circulating it. Members of the community therefore have developed a range of approaches and tactics to managing their online identities and involvement in fanfiction separately from other online activities. They participate predominantly pseudonymously or anonymously in activities around fanfiction and are often, rightly, wary of outside scrutiny, whether it be by journalists or academics. Having said that, this is also a community with a very strong identity, strong traditions of mutual support, and very much in the habit of theorising itself.

Social Media and the Digital Data Set:

Some of what I study is the fanfiction itself, which is published on authors’ personal blogs and websites, on social media platforms like LiveJournal and Tumblr, and in fanfiction archives such as fanfiction.net (FFN) and the Archive of Our Own (AO3). But I also study fan interactions and fan practices in these semi-public social media spaces. My data set therefore includes podcasts, comments left on fanfiction stories, conversations between community members posted on social media sites, and “meta” (commentary and analysis) which community members produce on topics ranging from the quality of writing in a TV series to in-depth examinations of social and political issues as represented in media and fanfiction. Because I have been a member of the community for nearly two decades, in many cases I also get privileged access to material which isn’t posted publicly, for instance locked LiveJournal posts or AO3 stories.

Things that keep me awake at night:

Below are three case studies of things gone wrong in fandom or online research, and the questions they raise for me.

Theory of Fic Gate: This was an incident in early 2015 where a class of undergraduate students were asked to leave comments on fanfiction as part of their assessment. They had little to no knowledge of the community, their standards, the rules of engagement. They were in fact specifically encouraged to leave a “critical” comment on the stories, something around which there are a lot of social rules within the fanfiction community. These comments caused a lot of upset to individuals whose writing was on the course reading list, as well as a lot of outrage within the fanfiction community who felt disrespected, and some ill will towards researchers and academia. The community organised quickly around one of the writers whose work was on the course reading list and engaged in more or less constructive debate with the course leaders and some of the students.

The incident raises some key questions for online and fandom researchers in general and for my research in particular. Who am I doing this research for? Who am I accountable to? As someone who is both a member of the fanfiction community and an outsider, how do I negotiate these two positions in a way that is respectful to the community, ethical, and still allows me to conduct my research with both quality and integrity?

At least part of the answer for me personally is that I feel accountable to the fanfiction community. I have a responsibility to them to treat them fairly and with respect. It is absolutely vital for me to be deeply familiar with the community and culture, their views and practices, their understanding of themselves and the world, before I engage them directly. This knowledge helps me engage the community respectfully, ask the right ethical questions, and make decisions about what material I expose to wider academic and public scrutiny. I am also working on ways to give the fanfiction community ways to feed back to me and have some control over the research, through my research blog, through interactions with interviewees, and through attending fandom conventions and speaking about my research.

Dalek half balls: “From Dalek half balls to Daft Punk helmets: Mimetic fandom and the crafting of replicas” is a published academic paper by a highly respected fan studies scholar and it makes some interesting points. It also cites and argues directly against theory written by a member of the fanfiction community, published on their LiveJournal. The paper addresses this LiveJournal post as if the two are on a level playing field with each other, ignoring power differentials. As with any other research, it is important to remember that there are power differentials between researchers and the people we study. Just because we can both stick up a blog on the internet and comment on each other’s posts doesn’t make us equal.

On the other hand, I am also increasingly coming to realise that on the subject I am studying - sexual consent - the fanfiction community produces distinct, extensive and nuanced knowledges not available in other communities or even in feminist academia. These knowledges are not in a format that academia would necessarily recognise, and there is considerable potential value in finding ways to disseminate them beyond their current context (though there are also risks involved in this). This raises huge questions about the role of the researcher in this space, and about the researcher’s relationship with the material and the community producing it. A lot of this material is theoretically rich and robust despite its unconventional (for academia) format. It feels wrong to simply treat it as “data”, to take it and put my own stamp on it. On the other hand, I believe it would also be wrong to treat this material and its authors as equal to theory and analysis published in a peer-reviewed journal and engage with it on that level, as that would hold it up to impossible standards.

Key questions for me to consider here: How do my choices of research subject and methodology reproduce or challenge power relations? How can I tweak those choices towards challenging and away from reproducing?

The Facebook Happiness Experiment: In June 2014, it was revealed that Facebook had manipulated users’ newsfeeds with the intention of manipulating their mood. While in my research I am not directly manipulating anyone or anything, I am in many cases conducting something that walks the fine line between covert and participant observation.

This raises some interesting questions. How much of the internet/social media platforms can be legitimately regarded as a public space? What are people’s expectations of privacy, how are they constructed and how are they managed? One common practice in the fanfiction community is privacy through obscurity: those in the know can find us, but most of the world has no idea. With increasing exposure of fanfiction in mainstream media, this expectation is becoming unrealistic, but that doesn’t necessarily mean that community behaviour and practices are always changing in line with these developments.

What is my responsibility as a researcher in terms of meeting those privacy expectations, and what are the practicalities around that? A significant issue for me will be quoting fan conversations and “meta” verbatim when a simple Google search can lead others back to the original source.

These are some of the questions that keep me awake at night. Perhaps the biggest insight for me here is that the vast majority of them are not asked on an ethics application form. While going through the ethics approval process has been a useful starting point for me, I have had to put in a lot of thought outside of and beyond the framework of that single form. There certainly aren’t any universal right answers for these questions, and some days I am not even convinced there is a single right answer for my particular research. There are simply different choices I can make, with as much consultation with the community as possible, while being aware of the power imbalances and responsibilities inherent in my position.

Getting to ‘Yes’ in the digital age

Last Monday (11^th May) the SRA, along with NSMNSS, hosted a seminar looking at ethics and informed consent in the context of online research. As long-standing network members will know, the ethical challenges of conducting research has been something that has consistently cropped up as a core concern for social scientists looking to use social media in their research, and this event demonstrated that this continued to be the case.

Matt Williams from the Social Data Science Lab kicked off proceedings with a discussion of his experiences of ethics in social media research based on his work with COSMOS, a platform for accessing Twitter data.

Matt focussed on some of the issues relating to publishing research based on Twitter data, and how Twitter’s policies relating to the publication of Tweets (showing names, @usernames, and unmodified Tweet text) can clash with researchers requirements of anonymity and protecting participants from harm, before outlining their approach to ‘risk assessment’ before publishing Tweets.

He also introduced some survey research suggesting that social media users were split in how concerned they were about their data being used for research, and that some types of users were more likely to be concerned than others. However, participants seemed to be less concerned about their data being used by universities than government or commercial organisations.

Following Matt (and some role playing!), Janet Salmons talked through some of her experiences of the best way of getting informed participation from potential research respondents in an online environment.

Janet emphasised the importance of building trust and credibility with research participants, and that different types of online communication actually provide opportunities to engage and inform participants; the key is thinking about who your target population is.

For those who missed out, or went and didn’t get everything down at the time, you can find copies Matt and Janet’s slides here and here, and Janet has also provided some additional resources about ethics and online research here.

As is often the case, perhaps the most interesting session was the Q&A at the end, chaired by NatCen’s Kandy Woodfield. The panel & audience discussed a range of questions covering topics such as the difficulties (and ethics) involved in removing participants once analysis has started (or been published!), whether consent can ever be truly ‘informed’, and whether participants need to be reminded of consent for passive (ongoing) observation.

Unfortunately (although perhaps not unexpectedly), there was not enough time to answer all of the attendees’ questions, so NSMNSS are going to be hosting a follow-up #NSMNSS Tweetchat on the ethics of online research on Monday 1^st June at 5pm (UK time).

If you have any questions that you would like to put to the NSMNSS community, please message us @NSMNSS, email us at nsmnss@natcen.ac.uk, or simply leave a comment below!

Picking a social media platform for research - our first Twitter chat of 2015

Missed out? Here’s the twitter feed from #NSMNSS chat on how to pick a social media platform in research

See below for the twitter feed from our first tweetchat of 2015 (Tues 3rd Feb) all about how to pick a social media platform in research.  Scroll to the bottom and work your way up to follow the conversation in the order it occurred. 

 

A summary of the 7 questions posed to those taking part is included below:

• Q1: What is a social media platform? #NSMNSS

• Q2: Which social media platforms are you using, or would like to use, in research? #NSMNSS

• Q3: Which platforms are you using to get data? #NSMNSS

• Q4: Do certain platforms lend themselves more to quantitative or qualitative approaches? 'Big data', 'small data'? #NSMNSS

• Q5: (from @jess1ecat) What difference is there in researching public data like Twitter stream cf. to group wikis & forums? #NSMNSS

• Q6: How do you handle data protection & ethical issues on different platforms? #NSMNSS

• Q7 How do we attend to our own online identities & use of social media platforms? #NSMNSS

Tweets about "#nsmnss since:2015-02-03 until:2015-02-04"

Thank you to those who joined us for the chat, it was an invaluable discussion. We hope you can join us for the next chat on Tues 3rd March 2015 5pm (UK time). All welcome! The voting poll to choose a discussion topic is here.

The changing nature of who produces and owns data: How will it impact survey research?

Brian Head is a research methodologist at RTI International. This post first appeared on SurveyPost on 20 May, 2014. You can follow Brian on Twitter @BrianFHead.

Survey researchers have become interested in big data because it offers potential solutions to problems we’re experiencing with traditional methods. Much of the focus so far has been on social media (e.g., Tweets), but sensors (wearable tech) and the internet of things (IoT) are producing an increasingly rich, complex, and massive source of data. These new data sources could lead to an important change in how individuals see the data collected about them, and thus have ramifications for those interested in gathering and analyzing those data.

Who compiles data?

Quantitative data about people have been gathered for millennia. But with technological advances and identification of new purposes for it, the past 100 years have seen significant increases in the amount of data produced and collected—e.g., data on consumer patterns and other market research, probability surveys, etc.

Common to these data are three factors: 1) the data are a commodity compiled, used, or traded by third parties; 2) generally there are no direct benefits to individuals about whom data are gathered; and 3) the organizations interested in the data gather, store, and analyze it. All this is not to say that throughout history individuals haven’t collected information about themselves. Individuals have collected qualitative data in the form of diaries and biographies. And, they have collected some quantitative data but this has generally to satisfy a third-party (e.g., collecting financial information to file taxes). But, now in addition to all of the data others compile about them, new technologies like wearable technologies (sensors) and IoT devices allow people to voluntarily produce and compile massive amounts of data about themselves and doing so can have a direct benefit to them. (Involuntary data collection through connected devices is already taking place—e.g., internet connected devices are being used for geo-targeting advertising).

Who owns or controls data?

Data are collected in different ways. Census data are collected periodically (intervals vary by nation) through a mandatory government data collection. Surveys generally operate under the requirement of voluntary participation, although there are exceptions.  Much of the consumer data gathered now is done surreptitiously. Examples include browser cookies that collect information about the websites we visit, search engines that collect information about the internet searches people conduct, email providers that scan emails, and apps that use geodata to market goods and services to prospective clients.

It seems the public is increasingly aware of and concerned with the sum of these data collections. According to a recent Robert Wood Johnson Foundation (RWJF) study large majorities of self-tracking app/device users think (84%) they do or want (75%) to own data that are collected with the device. There have been attempts to limit data collection, such as the recent attempt to limit the data the U.S. government collects on citizens.  Advocates of efforts like this tend to cite concerns over burden and privacy. The exponential growth of data collected both voluntarily and involuntarily through apps, sensors, and the IoT may cause similar (perhaps successful) attempts to change government and corporate policies to provide individuals more control over their data. In fact, market researchers are already beginning to respond to such an interest among consumers by offering to pay consumers for access to their browsing history, social network activity, and transactions they conduct online while at the same time giving those consumers control over which data they sell to the brokers.
As the amount of data collected about us increases, there’s a good chance individuals will increasingly see their data as their own, understand the value it has to various third parties, demand more control over it, and to be compensated for it. At first brush that may seem concerning. However, the type of compensation individuals’ desire for data will likely depend on how data will be used. For example, consumers are likely to continue to trade data for convenience in services (see thesis # 12). And, the RWJF report cited above suggests the usual leverages used to gain survey participation—e.g., topic salience and altruism—may work in gaining access to big data when the purpose of the study is for “public good research.”

Need for further research

Further research is needed in this area of big data to answer questions like: 1) to what extent, and how soon, will a larger proportion of the population begin to voluntarily use sensor and IoT devices; 2) will the general public continue to tolerate involuntary data collection when those data are collected by connected devices; 3) will the general public have opinions similar to early adopters in the RWJF about sharing personal data from connected devices with survey researchers; 4) will the leverages that work for gaining survey participation work for gaining access to personal big data or will new/additional leverages be needed; 5) will we be able to use techniques similar to those used to access administrative record data or will we need to develop new protocol for seeking permission to access these data? I look forward to seeing and contributing toward the research to answer these questions. What are your thoughts?

You Are What You Tweet: An Exploration of Tweets as an Auxiliary Data Source

Ashley Richards is a survey methodologist at RTI International. This post first appeared on SurveyPost on 29, July 2014. 

Last fall at MAPOR , Joe Murphy presented the findings of a fun study he did with our colleague, Justin Landwehr, and me. We asked survey respondents if we could look at their recent Tweets and combine them with their survey data. We took a subset of those respondents and masked their responses on six categorical variables. We then had three human coders and a machine algorithm try to predict the masked responses by reviewing the respondents’ Tweets and guessing how they would have responded on the survey. The coders looked for any clues in the Tweets, while the algorithm used a subset of Tweets and survey responses to find patterns in the way words were used. We found that both the humans and machine were better than random in predicting values of most of the variables.

We recently took this research a step further and compared the accuracy of these approaches to multiple imputation, with the help of our colleague Darryl Creel. Imputation is the approach traditionally used to account for missing data and we wanted to see how the nontraditional approaches stack up. Furthermore, we wanted to check out these approaches because imputation cannot be used in the case where survey questions are not asked. This commonly occurs because of space limitations, the desire to reduce respondent burden, or other factors. I will be presenting on this research at the upcoming Joint Statistical Meetings (JSM), in early August. I’ll give a brief summary here, but if you’d like more details on it please check out my presentation or email me for a copy of the paper.

Income was the only variable for which imputation was the most accurate approach, but the differences between imputation and the other approaches were not statistically significant. Imputation correctly predicted income 32% of the time, compared to 25% for human coders and 26% for the machine algorithm. Considering that there were four income categories and a person would have a 25% chance of randomly selecting the correct response, I am unimpressed with these success rates of 25%-32%.

Human coders outperformed imputation on the other demographic items (age and sex), but imputation was more accurate than the machine algorithm. For these variables, the human coders picked up on clues in respondents’ Tweets. I was one of the coders and found myself jumping to conclusions, but I did so with a pretty good rate of success. For instance, if a Tweeter said “haha” a lot or used smiley faces, I was more likely to guess the person was young and/or female. These are tendencies that I’ve observed personally but I’ve read about them too.

As a coder I struggled to predict respondents’ health and depression statuses, and this was evident in the results. Imputation was better than humans at predicting these, but the machine algorithm was even more accurate. The machine was also best at predicting who respondents voted for in the previous presidential election, with human coders in second place and imputation in last place. As a coder I found that predicting voting was fairly simple among the subset of respondents who Tweeted about politics. Many Tweeters avoided the subject altogether, but those who Tweeted about politics tended to make it obvious who they supported.


So what does this all mean? We found that even with a small set of respondents, Tweets can be used to produce estimates with accuracy in the same range or better[1] as imputation procedures. There is quite a bit of room for improvement in our methods that could make them even more accurate. For example, we could use a larger sample of Tweets to train the machine algorithm and we could select human coders who are especially perceptive and detail-oriented. The finding that Tweets are as good or better as imputation is important because imputation cannot be used in the case where survey questions were not asked.

As interesting as these findings may be, they need to be taken with a grain of salt, especially because of our small sample size (n=29).[2] Relying on Twitter data is challenging because many respondents are not on Twitter, and those who are on Twitter are not representative of the general population and may not be willing to share their Tweets for these purposes. Another challenge is the variation in Tweet content. For example, as I mentioned earlier, some people Tweet their political views while others stay away from the topic on Twitter.

Despite these limitations, Twitter may represent an important resource for estimating values that are desired but not asked for in a survey. Many of our survey respondents are dropping clues about these values across the Internet, and now it’s time to decide if and how to use them. How many clues have you dropped about yourself online? Is your online identity revealing of your true characteristics?!?

[1] Even if approaches using Tweets may be more accurate than imputation, they require more time and money and in many cases may not be worth the tradeoff. As discussed later, these findings need to be taken with a grain of salt.

[2] We had more than 2,000 respondents, but our sample size for this portion of the study was greatly reduced after excluding respondents who don’t use Twitter, respondents who did not authorize our use of their Tweets, and respondents whose Tweets were not in English. Furthermore, half of the remaining respondents’ Tweets were used to train the machine algorithm.

It started with a tweet...

Kandy Woodfield is the Learning and Enterprise Director at NatCen Social Research, and the co-founder of the NSMNSS network. You can reach Kandy on Twitter @jess1ecat.


It started with a tweet, a blog post and a nervous laugh. Three months later I found  myself looking at a book of blogs. How did that happen?! Being involved in the NSMNSS network since its beginning has been an ongoing delight for me. It's full of researchers who aren't afraid to push the boundaries, question established thinking and break down a few silos. When I began my social research career, mobile phones were suitcase-sized and collecting your data meant lugging a tape recorder and tapes around with you. That world is gone, the smartphone most of us carry in our pockets now replaces most of the researcher's kitbag, and one single device is our street atlas, translator, digital recorder, video camera and so much more. Our research world today is a different place from 20 years ago, social media are common and we don't bat an eyelid at running a virtual focus group or online survey. We navigate and manage our social relationships using a plethora of tools, apps and platforms and the worlds we inhabit physically no longer limit our ability to make connections.

Social research as a craft, a profession, is all about making sense of the worlds and networks we and others live in, how strange would it be then if the methods and tools we use to navigate these new social worlds were not also changing and flexing.  Our network set out to give researchers a space to reflect on how social media and new forms of data were challenging conventional research practice and how we engage with research participants and audiences. If we had found little to discuss and little change it would have been worrying, I am relieved to report the opposite, researchers have been eager to share their experiences, dissect their success at using new methods and explore knotty questions about robustness, ethics and methods.

Our forthcoming  book of blogs is our members take on what that changing methodological world feels like to them, it's about where the boundaries are blurring between disciplines and methods, roles and realities. It is not a peer reviewed collection and it's not meant to be used as a text book, what we hope it offers is a series of challenging, interesting, topical perspectives on how social research is adapting, or not, in the face of huge technological and social change.

We are holding a launch event on Wednesday 29^th October at NatCen Social Research if you would like more details please contact us.

I want to thank every single author from the established bloggers to the new writers who have shared their thoughts with us in this volume. I hope you enjoy the book as much as I have enjoyed curating it. Remember you can follow the network and join in the discussion @NSMNSS, #NSMNSS or at our http://nsmnss.blogspot.co.uk/

New Social Media, New Social Science… and New Ethical Issues!

We held a small event on Friday 21st February 2014, our goal was to have a series of focused discussions around the ethical dimensions of social media research and to come up with a series of action points for the network to take forward. The day also included two presentations of related research by network members. You can read a a storify of the day - sfy.co/rPSZ 

We will post more about the outcomes and discussions shortly but we want to kick off by sharing links to the two reports and presentations. A team from NatCen has been researching the views of social media users on how their posted data should be handled by researchers. The findings are illuminating and will help to inform how we consider we should work with social media data in the future. You can read a post by the research team here, and then the findings here.

Now Janet Salmons introduces the research she has undertaken on what researchers need to help support their ethical practice when conducting social research online:

Our NSMNSS network has convened researchers from the UK and around the world in thought-provoking dialogue on topics related to scholarly use the Internet and social media. Recurrent matters related to research ethics demonstrate that there are many questions and concerns about how to adapt conventional guidelines to kinds of online research. In the atmosphere of collaboration and exchange NSMNSS encourages, resources are often suggested.  My curiosity led to two questions: to what extent do the resources suggested by the NSMNSS network address the concerns and questions raised by the NSMNSS network? What are the gaps and how can or should they be addressed? The report, “New Social Media, New Social Science… and New Ethical Issues!” is the result of this exploration. 

Numerous concerns and queries emerged from network discussions, classified here as seven interrelated themes:

• Participants: Issues related to online sampling and recruiting to find, screen, and select appropriate and verifiable research participants.

• Identity: Issues related to the identity, anonymity and/or privacy of the participant andthe researcher.

• Research site: Issues related to the setting for the study or source of data.

• Informed consent: Issues related to the determination of when consent is needed and what type of consent is adequate.

• Data: Issues related to user-generated content and ownership and protection of data.

• Research guidance: Issues related to the academic institutions and committees that prepare the next generation of researchers and must approve researchers’ proposals or decide whether their research is adequate for tenure or promotion.

• Methods and methodologies: Issues related to implications of social media research for the ways we think about research methods and methodologies.

The first five themes relate specifically to the designing, conducting and reporting on research. The final two themes raise larger issues for the field—a field NSMNSS members characterize as multidisciplinary.

Many of the recommended guidelines and materials offered little or no advice about online research ethics. However, a few professional societies and organizations have made the effort to either create a set of guidelines specific to research on the Internet, or have created supplementary materials that focus on how to apply that profession’s ethical standards when conducting studies online—and reporting on the findings. Examples of the latter were chosen for this review including materials from the Association of Internet Researchers(AOIR), British Educational Research Association (BERA), British Psychological Society (BPS), CASRO, European Society for Opinion and Marketing Research (ESOMAR) and Market Research Society (MRS), and Association (MRA).

As you can see, in some cases the profiled guidelines make recommendations aligned with NMSNSS network needs and in other cases they instead identify other risks and concerns.

You can read the full report here or watch the presentation below.

Please use the comment box to add your thoughts, relevant experiences, or to suggest other resources. We are also planning a Tweetchat discussion of the report on Tuesday 11th March at 7pm GMT (8am NZDT/6am AEDT/8pm CET/9pm SAST/3pm EDT/1pm MDT), so please join us ! You can read more about taking part in an NSMNSS twitter chat here.

Project learning points from a new researcher: users’ views of social media research

Hannah is a researcher at NatCen Social Research, a non-political charity that specialises in social policy research. Before joining NatCen as a graduate research trainee in September 2012, she worked as an Employment Adviser to the long-term unemployed. Hannah is now based in NatCen’s Income and Work team and is involved in survey maintenance and smaller scale qualitative projects. Her research interests lie in poverty and disadvantage, and also now in social media use! You can follow Hannah on Twitter by searching @h_silvester.

Last year I was one of eleven lucky graduates taken on by UK based NatCen Social Research. To get hands on experience –and to make mistakes in a controlled environment! -we were given a year to develop and run a study with only minimal guidance from senior staff. Now nearing the end (we’re writing our report), we’d like to share some learning points.

As well as specializing in independent social policy research, NatCen has always prided itself on methodological innovation. For example it has recently set-up with partners the ‘New Social Media, New Social Science’ network to look at what opportunities social media research can provide. The network and NatCen are particularly interested in the use of social media websites and ethical practice when researching online.

Taking these two interests one step further, our graduate project looked at what users of social media think about the ethics of research when it uses their posts and other information. So now let’s take a frank look at the key things we learnt while working on this qualitative, exploratory study.

Definition, definition, definition!

While it’s normal for potentially interesting side issues to crop up, or for other areas to be discounted, you should develop the focus of your research as early as possible and stick to it. Having a clear research focus will make creating the topic guide (interview schedule) easier and will influence your analysis and report planning.

Define key terms: again, choose as early as possible. Terms should preferably be ‘current’ elsewhere. We argued considerably over ‘social media websites’ vs. ‘social networking sites’ and our report editor is still exasperated we’re referring just to ‘sites’! We also had to decide between participants, respondents, people and ‘social media users’ (the latter won) –the more precise the better!

‘I work better the night before a deadline’

Allow yourself realistic time to complete a task if it’s your first time doing it, but don’t then fall into the trap of thinking ‘I’ve got aaages yet! –no one truly works better the night before a deadline!

Order, order!

Have someone (preferably the project lead) draw up an agenda (and more importantly, stick to it!) for each meeting and limit the meeting time. This will help make sure any discussion is concise and to the point.

Don’t be too democratic

While it might seem fair that everyone in the project team is given a chance to  comment on written outputs, the old adage ‘too many cooks spoil the broth’ is definitely true! Instead, we found that an initial set up meeting, for parts of the project like drafting the topic guide, is helpful to generate ideas that are then consolidated and written up by one member. The chosen project manager will then ultimately have the final say and editing duties.

Recruitment

We were able to recruit from an established sample (used previously for NatCen’s renowned British Social Attitudes survey). Because the survey had already asked participants about their internet use, we had good information on key sample criteria and could target our invitation letters. Unfortunately we found that the sample was too shallow once we’d set our primary/ quota criteria (we wanted a third of the sample to be ‘low’ internet users, a third ‘medium’ users and the rest ‘high’ users). While sometimes quotas may need to be revised we decided to fall back on our contingency plan: to use a recruitment agency. It was a little scary letting go of control and we had to emphasise our criteria a number of times, but in the end we got the right people to take part at the right time!

So, those are the learning points I want to leave you with and I hope they’ve been helpful. If you’re considering using social media websites in your work, our findings will hopefully help people think about how they carry out this kind of research. If you’re keen to find out how, and you really can’t wait until December (I don’t blame you), do read this blog for our interim findings and feel free to email me with any questions!

 This Post was first published on http://socphd.wordpress.com/