Tuesday, 15 April 2014

Back to University: Summary of ‘Research Ethics into the Digital Age’ Conference

Kelsey Beninger is a researcher at NatCen Social Research.

Recently I was invited to speak at Sheffield University’s ‘Research Ethics into the Digital Age’ Conference. It was an exciting opportunity, not in the least because it involved a swanky pre-conference speaker’s dinner. But really, it was exciting because the University was celebrating ten years of its research ethics committee and was launching their new purpose-built online ethics submission portal. Paper-based applications, be gone!

Usually at these type of ethics and internet mediated research events there are a diverse bunch of cross discipline and cross institution technicians, practitioners, ethical specialists, to name a few. This event had a diverse audience but in a different way; they were mostly from Sheffield University. The great turnout demonstrated how there was not only commitment to high ethical standards, but actual interest from across departments and job roles at the University. I met a few administrators that manage the huge numbers of ethics applications, members of the university research ethics committee, and students and professors galore!

The morning had a great line up of key note speakers. Professor Richard Jenkins from Sheffield University provided a nice overview of ethics in international projects around three themes:

  1. data must satisfy the host country’s legal and ethical requirements,
  2. data must satisfy your university’s REC policy, and
  3. data must satisfy the professional standards of the profession you are associated with.
Some obvious but important key points included knowing the specific cultural, legal and social laws of the country you are going to research in before you get there and keep a detailed paper trail of everything you do. Also, you share risks with any collaborators so if they don’t have governance framework in their country then discuss it early and encourage the application of your UK standards. The moral of the story: the ethical situation is more complex with international research but the responsibilities you have as a researcher with respect to ethics are the same.

Professor Joe Cannataci from the University of Malta cut the legal jargon and conveyed important points about data protection and the use of personal data from the internet. He drew on an intriguing array of international projects (one of which may have involved a funny story of him dancing his entrance to gain acceptance when meeting a rural tribe in Malaysia). He started his presentation by discussing the principle of relevance in data protection law. This is something many of us in research are familiar with- collect only the right data, collected only by the right people, at the right time and used by the right people in the right way for an agreed time. Say that 10 times fast! Of particular relevance to researchers beginning studies across Europe is knowing where the data is to be stored because there are different data protection laws in European countries compared to EU countries.

Next up was Claire Hewson from the Open University. Claire provided an overview of the challenges associated with the ethics of internet mediated research. A point that got me thinking ‘Is there truly an ‘unobtrusive’ type of data collection?’ was her distinction between obtrusive and unobtrusive methods. Obtrusive are activities such as actively recruiting individuals and those individuals knowingly partake in research. Unobtrusive methods included big data, data mining, and observations. It’s only unobtrusive because people are not aware of it in the first instance. It would become pretty obtrusive to some if participants were cognisant of what was being done with their personal data. A nice take away point from the presentation was that ‘thinking is not optional’ when it comes to applying ethical frameworks to changing online environments.

After a tasty lunch in Sheffield University’s lovely new student union building my turn was up! I delivered a session on the challenges of social media research, drawing upon recent exploratory research with users of social media (http://www.natcen.ac.uk/our-research/research/research-using-social-media-users-views/) about their views on researchers using their data in their work. I also drew on the work of the network and the survey conducted by network member Janet Salmons on researcher and practitioner views of the ethics of online research. My group explored the challenges associated with three themes: recruitment and data collection; interviewer identity and wellbeing; and analysis and presentation of data. Summarising key points that we as researchers are familiar with, I pushed the issues home by using direct examples from our exploratory research.

We wrapped up with a section on recommendations including only using social media in research if it is appropriate for your question; being transparent with participants and other researchers about risks of the research and the limitations of your sample; taking reasonable steps to inform users of your intention to utilise their data in research. Read the full list of recommendations in the report, here.

Thursday, 20 March 2014

The contribution of social media to human resource management


Zhao, Tianzhang is a student in the Social Media MA at the University of Westminster.

Social media helped to generate energy and mobilize a community of support in the U.S. presidential election in 2008, which helped Barack Obama to achieve popularity (Jue, et al., 2010). According to Jue and his colleagues (2010), this fervor of political influence would be of particular value to any community activist, no matter their political beliefs or organizational affiliation.

If this were true what would this mean for organisational management? Most organisations seek to engage employees, clients, customers, suppliers and partners in an effort to achieve brand loyalty to their products and services. However, in today’s world political and business leaders cope with increasingly difficult circumstances in achieving these objectives (Jue, et al., 2010).

What to do? Well, social media is a useful platform for leaders to construct and share their strategic goals in a relatively efficient and accessible way. To gain and sustain competitive advantage, leaders need to rely on the engagement and commitment of those they work with, namely their employees and partners. They also could depend on social media platforms to accelerate and enhance employee innovation, engagement, and performance (Jue, et al., 2010); The elements of human resource management in an organization. In other words, social media

As Jue and his colleagues (2010: 2) claimed, “those who are actively using social media in their organizations can be confident that they have new ways to improve their business performance, create long-term capability, and ultimately sustain their success”.

Based on Jue and his colleagues’ work (2010: 74-75), social media would be a great help at work, which would be reflected in the following ways:

  1.  Incorporated into a company’s corporate culture and critical to its strategy.
  2. cost effective.
  3. scales more effectively to meet a global audience’s training needs.
  4. engages employees in sharing knowledge and expertise.
For example, we can look at the NHS. In practice, NHS states that social media helps them enhance their human resource efficiency. In their 2013 report on their employers, it was pointed out that firstly, social media offers a great platform for both organizations and individuals to listen and have conversations with people they want to influence and talk to. Secondly, social media provides an online platform for HR managers to highlight the working behavior guidance and HR policies. Thirdly, the next generation of NHS employees would rely on getting information from the internet and mobile devices, therefore, how NHS embraces these social media users for the benefits of employees and patients would be significant in developing a sustainable NHS. Finally, if NHS could trust their employees with the patients’ lives, why can employees not be trusted on social media?

To sum up, the relationship between social media and human resource management has an unexpected change in this dynamic environment. For social media researchers, it should be emphasized that the unexpected function of social media would always emerge along with the changing environment in specific industries or working areas. For HR managers and leaders, it is time to be aware of the importance of social media’s impact at work, and think about how to take the advantage of using social media effectively to develop the organization and promote business performance.

References

CIPD (Chartered Institute of Personnel and Development). (2013). The role of HR in corporate responsibility. Available: http://www.cipd.co.uk/binaries/6100%20SOP%20Corporate%20Responsibility%20(WEB).pdf. Last accessed 1st Dec 2013.

Jue, A.L., Marr, J.A. & Kassotakis, M.E. (2010). SOCIAL MEDIA AT WORK: How Networking Tools Propel Organizational Performance. United States of America: Jossey-Bass.


NHS. (2013). HR and social media in the NHS. Available: http://www.nhsemployers.org/Aboutus/Publications/Pages/HR-social-media-NHS.aspx. Last accessed 1st Dec 2013.

Thursday, 13 March 2014

Social Media – Giving sport stars a voice?


Abdullah Anees
 is a student in the Social Media MA at the University of Westminster.

Two things I am very fond of are social media and sports, and what better way to relate the two in modern day then a reflective blog on how one influences the other.

As we all know, social media platforms have allowed people to voice their opinions with others worldwide. The difference in a message being shared from any individual to the larger audience has developed at a furious pace since the development of Web 2.0. We now see people, such as athletic celebrities, who we were once accustomed to only seeing on the TV, now becoming vocal on social media platforms. It seems stars are taking their views more public rather than leaving that up to their publicists.

Twitter, Facebook and various other social media platforms have allowed athletes to more readily reach out to their fans to establish a common connection. This common connection is the will to express their opinions and views; they now have a stage to show they have another side to them apart from sports. TV and Newspapers did not really give them a stage to express views on certain issues; and many times they were miss-represented without having a way to reply.

If newspapers and television pick and choose information from these athletes then surely social media allows us to eliminate the press and obtain information directly from these stars? Social media has given people access to direct sources of information in every possible field.

Social media has given the space for these public stars needed to protect their image in times where a candid photograph or a quote could be exploited and taken out of context.

Does a social medium really give them freedom of speech?

Many sport stars have gone on to twitter to express their views on certain events and have received mixed reactions from the online community. This has resulted in them retracting statements made online by deleting posts and tweets. Being in the ‘public eye’ they are expected to behave in an appropriate manner, questioning their actual freedom of opinions.

Being role models of many young children globally, their views and behaviours are constantly monitored on social platforms and you get the feeling the press is ready to pounce on any slip up these stars make. The press will always build stories around sports stars expressing their views and opinions socially.

Another angle I want to mention is the commercial aspect of sport stars being on social media. If a top flight footballer tweets a picture of his branded boots is that a message from his sponsors? Do they really have total control over their tweets? Even in the case of false advertisements from companies who deny they get sponsored athletes to promote to their audience their brand it still has to be questioned.

There are some sports stars that I would love to see on social platforms; however there are numerous reasons why they keep away. Their inability to cope with the ‘digital public eye’ and what they might feel are restrictions of speech being a public figure would be my first opinion.


Would you like to reflect on your research, pose ethical or logistical research questions to the network, or blog about developments in the field of new social media? See your name in print by emailing nsmnss@natcen.ac.uk 

Wednesday, 5 March 2014

Keeping up with technology: What is “scientific lag” and can we proactively reduce it?

In 2011 then Census Director Robert Groves wrote on the Census Director’s Blog about the burgeoning volume of “organic data”—data that, as opposed to “designed data,” have no meaning until they are used (surveys are a primary example of the latter). He noted that finding ways to combine these two types of data to increase the “information-to-data ratio” was a challenge, but also represented the future of surveys. Using terms identified as “big data descriptors” in Groves’ piece, as well as a few other terms I think qualify, I put together the graph below to show the number of AAPOR presentation titles between 2010 and 2013 that contain a big data descriptor.1,2
big data descriptors in AAPOR presentation titles 2010-2013
One take away is the increased interest researchers have shown in big data over the past few years. An equally important lesson is that almost all of the attention big data has received from AAPOR members—at least measured by the number of presentations they’ve done—has been on social networking sites (SNS). I found only one presentation in the past four AAPOR conference programs that contained a big data descriptor for a non-social media topic—a demonstration in 2012 by Ben Waber on the use of wearable sensors for measuring behavior.
To some extent this is explained by scientific lag. Just like there is cultural lag—the time between the emergence of a new technology and when culture catches up—there is a lag time between when consumers adopt technologies and when our research methodologies catch up (i.e., scientific lag = cultural lag + time until research methodologies using those technologies are implemented). And, technologies often don’t remain static, but rather evolve making it a continuous game of catchup (development) for research methodologists. I’ll go into more detail about this in a presentation I’m giving at the AAPOR conference this year, but one quick example from the annals of survey research history is the development of computer-assisted telephone interviewing (CATI). While telephone exchanges had existed for almost a century and programmable computers emerged in the 1940s, it took until 1971 for CATI systems to be developed by market researchers, another five years for academic researchers to begin using it, and the federal government another seven years to implement its use. Certainly, cultural lag played a role. It took years for enough households to have telephones for probability based telephone sampling to make sense. In addition, it took time for the programmable computer to develop into a device usable for this purpose. But, it also took researchers time to figure out such a system was possible and the value it presented.
Now, let’s fast forward a bit. In 1997, one of the first SNSs, sixdegrees.com, was created.  It lasted until 2001. A host of other networking sites, the ones most of us are familiar with, sprang up in the early 2000s—Myspace (2003), Facebook (2004), and Twitter (2006). There are, I suppose, two ways of looking at the cultural and scientific lags and SNSs. On the one hand, it took a few years SNSs to grow to significant numbers. For example, it took Facebook four years (2004 – 2008) to grow to 100 million users. Within four years of that development there were multiple presentations at AAPOR on the subject. That’s certainly much faster than the development of CATI technology/adoption. On the other hand, social researchers took nearly a decade from the birth of widely popular SNSs to begin formally recognizing their research utility.
Now, we may be at the cusp of another such tsunami of consumer technology adoption. Groups disagree on the exact timing (e.g., Forbes says 2014 and MIT Technology Review says 2013), but the evidence points to the start of rapid growth in the use of internet connected sensors and devices for a multitude of purposes. I’ve recently written about how and why I think the devices and the IoT will affect social science data collection.
My question is whether the research community can be more proactive, and therefore decrease the scientific lag between adoption and research implementation. My hope is we will and that it will have a positive effect on survey data collection.
I’ll be presenting more thoughts on this topic at AAPOR and look forward to the discussion we have about big data in the session. Between now and then I’d welcome the thoughts others have on or experiences others have had with using wearable tech, sensors, or the IoT for research.
This was first posted on Survey Post  on 24/02/14
Brian Head is a research methodologist at RTI International with 5 years of experience in the government and not-for-profit research sectors.  Training in sociology and research methods and statistics led him to a career in research where his work has included questionnaire design and evaluation,  managing data collection efforts, and qualitative and quantitative data analysis.
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    Monday, 3 March 2014

    Get chatting on social media research ethics: Upcoming Tweetchat, 11 March 2014


    Last week we shared a post with links to a report based on an analysis of NSMNSS network members' perspectives and questions, and a review of some prominent ethics guides (See the NSMNSS blog post from 27 February). 

    Discussions of ethical principles and guidance related to social media research are plenty, and thrilling! But what do you think? What questions do you have about your own research or about the studies your students propose? What do you hope to find in the ethics guildelines you consult? How can we, as an emerging field, strengthen the ethical basis of social media scholarship to improve overall credibility? 

    You can join us for a Tweetchat on these very questions and related issues by following #NSMNSS on Tuesday 11 March 2014 at 7:00pm (London time) or 3:00pm in New York time. (See www.timeanddate.com for your time zone.)

    Remember to include #NSMNSS in all your posts to help us capture all of the discussion. We will provide a transcript of the Tweetchat on our blog following the event. 

    Friday, 28 February 2014

    Using “Small Data” to Improve the Use of “Big Data”

    Digital Globe
    This post was first published on Survey Post on Feb. 3rd, 2014.
    Recently, I attended two statistical events in the Washington, DC, area: one was the 23rd Morris Hansen Lecture  on “Envisioning the 2030 U.S. Census”; the other was the SAMSI workshop on “Computational Methods for Censuses and Surveys.” “Big data” was a popular keyword at both events and stirred up discussions on how to utilize it (such as from administrative records and online data sources) for current government statistics, especially when combining big data with  traditional survey data.
    Statisticians are exploring new ways in which big data can be used. The US Census has initiated investigations on using administrative records in the 2020 Census. The National Center for Health Statistics (NCHS) has identified some research opportunities combining multiple data sources. University-based researchers  have launched studies on the use of Google trends and other online data in small area estimation.
    When big data dominated the mainstream discussion at these events, I started thinking more about “small data.” Can small data help us make better use of big data? Here are some of my thoughts.
    1. Applying a conventional sampling-based approach to big data: more and more administrative records are collected electronically. Statisticians are excited about using these records that may contain information from the entire population for analytic purposes. Literature in the past two decades has extensively discussed the advantages of administrative records. Processing administrative records data, however, can be quite time consuming. In addition, it can be cumbersome to run analyses on these large datasets because of the large data volume. Especially, when analysts use conventional statistical software, such as SAS, Stata and R, it becomes increasingly complex to handle, store and analyze these data. The question is: is there a way to reduce the data volume and increase computational speed? Applying conventional sampling-based approach (e.g. optimal sampling, calibration weighting) may make a big data smaller and more manageable while allowing researchers to maintain decent data quality.
    2. Combining non-probability sample data with probability sample data: many big data, such as data collected by Google/Twitter/Facebook, are not census (population) data. We may treat them as non-probability sample data.  Elements are chosen arbitrarily in these datasets and there is no way to estimate the probability that each element in the population will be included. Also, it is not guaranteed that each element has a chance of being included, making it impossible either to assess the validity (always measured in terms of “bias”) and reality (always measured in terms of “variance”) of the data. One solution to make the data more representative of the entire population is to combine them with probability sample data (e.g. survey data), which can be relatively smaller. This method can also assist us estimating sample variability and identifying potential bias in big data.
    3. Using high-quality small data for measuring and adjusting errors in big data: big data is not only non-representative of the target population, but also carry loads of measurement errors because the construct behind a particular measure in these data can differ from the construct that analysts require. To evaluate errors in the big data and improve precision, small survey data can be collected for validation. Take the National Health Interview Survey (NHIS) as an example. This is a household interview survey with only self-reported data. To improve on analyses of the NHIS self-reported data, an imputation-based strategy for using clinical information from an examination-based health survey (i.e. National Health Nutrition Examination Survey, NHANES) was implemented that predicts clinical values from self-reported values and covariates. Estimates of health measures based on the multiply imputed clinical values are different from those based on the NHIS self-reported data alone and have smaller estimated standard errors than those based solely on the NHANES clinical data. Similarly, we may assess potential errors in big data through a more sophisticated and accurate small survey.
    While big data provides us massive and timely information from various sources (e.g. social media, administrative records, small data is simple, easy to collect and process, and can be more accurate and representative.  Can small data help you when dealing with your big data problems?


    Dan Liao is a research statistician at RTI International. She currently works on multiple aspects of data processing and  analysis for large, multistage surveys of health care in the United States, including sampling design, calibration weighting, data editing and imputation, statistical disclosure control, and the analysis of survey data. Her survey research interests include multiphase survey designs, combining survey and administrative data, domain estimation, calibration weighting, and regression diagnostics for complex survey data. Dan has a PhD in Survey Methodology from the Joint Program in Survey Methodology at University of Maryland and has published research focusing on regression diagnostics, calibration weighting and predictive modeling.

    Annual SRA conference on social media in social research

    call for papers advert
    The 4th Social Media in Social Research event is being held on the 16th May in London, it would be great if lots of network members submitted papers so please do get your thinking caps on. 

    The call for papers closes on 10th March.



    We'd like to start sharing news about network members who are presenting social media research papers at upcoming conferences, so please let us know if you're presenting at this or other conference by adding a comment here or tweeting @NSMNSS.