On 11th October NSMNSS and
the SRA co-ran an event looking at social media research tools. Speakers came
from a range of backgrounds, and discussed mix of qualitative and quantitative
methodologies including text, image, network, and geographical analysis. All
slides can be found here http://the-sra.org.uk/events/archive/ and presenters will be contributing to a blog series
about social research tools, due to be released later this year, so keep your
eyes peeled!
Steven McDermott kicked things off by
discussing the idea that ‘data is an ideology- a fiction that we can’t take at
face value’. In his session Steven not only discussed which tools he used, but
urged researchers to critically engage with the information we get from these
tools, and what biases they may carry. He concluded that social media data
should be used as an ‘indicator’ (rather than a fact) alongside other methods,
such as ethnography, in order to get the ‘full picture’.
Next, Wasim Ahmed talked about NodeXL, a free Microsoft Excel plug-in he uses for twitter analytics, but can also be used with Facebook, Instagram and more! The main focus of this session was the graph function of NodeXL, which allows the mapping of networks. The tool also has a graph gallery, which allows users to access historic data stored there. NodeXL is a free tool and very user-friendly according to Wasim, so he recommends downloading and having a look at mapping your own data.
Moving on to developing tools for social
media analysis, Luke Sloan from the COSMOS introduced their analysis tool. Luke
started off by saying that the programme was created for researchers who ‘don’t
understand technology’ meaning that complex computing language is not required
to use it. Like NodeXL, COSMOS is also good at mapping, and can break down
tweets by geography, gender and time, as well as identifying popular words and
phrases in tweets; particularly useful for content and sentiment analysis.
Philip Brooker then discussed social media analytics
using Chorus. The majority of the session was interactive, with Philip
demonstrating how to use Chorus with twitter data. Chorus allows users to
retrieve data from twitter by searching for hashtags and phrases. A good
element of this tool is that it allows users to continually add data, allowing
for longitudinal datasets to be created. It also has a timeline function which
can be used to see the frequency of tweets alongside different metrics (again,
very useful for sentiment analysis). There is also a cluster explorer function,
which allows users to see how different tweets and topics interact with each
other. A function which will allow for gathering of demographic information
from twitter profiles is also currently being developed.
There were a couple of sessions on using
social media for qualitative analysis; the first from Gillian Mooney was on
using Facebook to conduct and recruit for research. Gillian emphasised that
Facebook is good for stimulating discussion and debate, but she also identified
a few drawbacks in the practical and ethical implications. Recruitment seemed
to have been slow moving via Facebook, and Gillian suggested that twitter may
be a better way of recruiting participants. She also stated that there are
wider ethical implications with Facebook research because it often means that
the researcher actively participates with the platform, which blurs the line
between the researcher and participant. While this makes ethical research more
difficult to conduct, she believes that it makes for more vibrant research. She
ended with a call for ethical boards to be more understanding of social media
research, and for a clear and consistent research ethics framework across all
platforms.
Sarah Lewthwaite continued with qualitative
analysis, by talking about developing inclusive ‘digital toolboxes’ so that
research is accessible to all. Sarah stated that online research must be made
accessible to all people in order to get a better sample and more vibrant data.
While web accessibility is becoming more of a legal requirement for social
media companies, there are still gaps in accessibility across platforms, and we
therefore need greater technological innovation for social media and research
tools. Sarah Lewthwaite used the ‘over the shoulder’ method (using a remote
desktop and screen sharing) to observe how some people with disabilities access
and use social media.
Our final group of sessions was on image
analysis.
Francesco D’Orazio discussed image (and
more specifically, brand) coding and analysis using Pulsar, which works across a
range of social media platforms, including twitter and Instagram. To conduct
the analysis, an algorithm must be created, alongside human coders, to define
certain concepts (i.e. image topics), search images, and tag them with the
concepts before clustering them. Francesco believes that doing this form of
image analysis can do more for a brand than simple logo detection.
Finally, Yeran Sun discussed using images
to map tourist hotspots. Yeran used Flickr (an often ignored platform for
research), and geo-clustered images via their meta-data using R and QGIS (free
and open to use) to show popular tourist destinations. Often, images will have
longitude and latitude tags, which allow for precise mapping. If used
effectively, geo-tagging such as this can be used to provide the ‘best’ route
for tourists to see all the popular hotspots, or inversely, create
‘alternative’ routes for those who wish to stay away from popular tourist
sites!
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