Researching Social Media: A Practical Overview. Delivered at a workshop on Social Media theory and practice at the University of Sheffield. Tools that were outlined were Mozdeh, TAGS, COSMOS, Chorus as well as DiscoverText and NodeXL Pro.

1. Social Media: A
Practical Approach
Wasim Ahmed (BA, MSc)
@was3210
wahmed1@sheffield.ac.uk
Tuesday 30th of May 2017
Researching Social Media: A Theoretical and Practical
Overview - University of Sheffield

2. About me
• Third Year PhD student in the Health Informatics Research
Group, Information School, University of Sheffield. (Faculty
Scholarship).
• Worked on a number of projects teaching and researching
social media.
• Run an analytics blog with readership in over 136 countries.
Read across media, government, and academia.

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https://wasimahmed.org/about/
http://blogs.lse.ac.uk/impactofsocialsciences/?s=wasim+ahmed
Published a number of
research papers, and
blogged widely.

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• Twitter has over 313 million monthly active users1 –
citizens can use this channel to express their views.
• Research on Twitter has the potential to cut across many
disciplines.
• Questions arise over how to obtain and analyse social
media data.
1 https://about.twitter.com/company
Twitter for Academic Research

5. Twitter as a Consumer Panel
• According to one statistic there are on average 6
thousand tweets a second!
• So around 350,000 tweets are sent every
minute.
• Which makes it around 500 million tweets per
day.
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6. Social Media Platforms
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0
200
400
600
800
1000
1200
1400
1600
1800
2000
Number of Million Monthly Active Users

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• Open API so anyone with an Internet connection can
retrieve data.
• Open platform where anyone can follow anyone and can
request to follow other users.
• A lot of meta-data fields available to developers to
create analytics apps.
Why is Twitter so popular?

8. Social Media Platforms
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• Facebook (1.871 billion monthly active users)
• YouTube (1 billion monthly active users)
• Instagram (600 million monthly active users)
• Twitter (317 million monthly active users)
• Pinterest (150 million monthly active users)

9. Twitter API
• Twitter’s Search API (free)– is a sample of
tweets so some tweets and users may be
missing from results. This is free, but limited to 7
days back in time.
• Firehose API (paid) – in theory, 100% of Twitter
data. This can be costly.
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10. How do you retrieve data?
• Use a keyword e.g., Ebola
• Use a hashtag e.g., #EbolaOutbreak
• Use a Twitter handle e.g., @was3210
• Combine search queries using AND or OR
operators.
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11. Types of Analysis
• Content Analysis
• Thematic Analysis
• Network Analysis
• Machine Learning
• Sentiment Analysis
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Tools Covered in this Presentation
• DiscoverText
• NodeXL
• Chorus
• Mozdeh
• TAGS
• COSMOS

13. DiscoverText
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• This presentation will focus on the potential of
DiscoverText for analysing Twitter data for academic
research.
• However, there are many more potential uses of
DiscoverText

14. DiscoverText used in…
• Consumer industries
• Education
• Human Resources
• Legal
• Medical & Pharma
• Government
• Military
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15. DiscoverText as Data Science
• DiscoverText has a number of very powerful text
mining, human coding, and machine learning
features
• Access to the free Twitter Search API data
• Access to premium Gnip PowerTrack 2.0
Twitter data
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16. Fiver Pillars of Text Analytics
• Search
• Filtering
• De-duplication and Clustering
• Human Coding
• Machine-Learning
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17. For a topic overview you could
• Retrieve Twitter data on a topic of interest
search and filter out non-relevant data.
• Generate duplicates and near-duplicate
clusters.
• This would allow you to more easily code
the data.
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18. Filtering Data
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19. DiscoverText has Active Learning
• You can manually code a sub-set of data
in DiscoverText then allow a machine to
code the next iteration
• You can check for quality (adjust coding
parameters) and run the cycle again
• So humans and machines work together
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20. An example: Manchester Derby
• During a football game users were tweeting
about a buzzing sound, and some were not
happy with Sky’s camera angles
• You could use DiscoverText to filter the
data
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Import Twitter data

22. Applying Text Analytics
• Search for ‘buzzing’, ‘noise’, and ‘camera’
• Find positive instances (‘what’s that buzzing
noise from Sky?) and also negative e.g., people
‘buzzing’ from the game, or which team is
making the most ‘noise’
• Generating clusters and coding the data
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23. Importance of Generating Clusters
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24. #WorldMentalHealthDay

25. • Most frequently shared URLs, Domains, Hashtags,
Words, Word Pairs, Replied-To, Mentioned Users, and
most Frequent Tweeters.
• Produces analytics overall and by group of users (users
are grouped by tweet content).
• By looking at different metrics associated with different
groups (G1, G2, G3 etc) you can see the different topics
that users may be talking about.
NodeXL Produces a Number of Analytics

26. [Divided]
Polarized Crowds
[Unified]
Tight Crowd
[Fragmented]
Brand Clusters
[Clustered]
Community Clusters
[In-Hub & Spoke]
Broadcast Network
[Out-Hub & Spoke]
Support Network
6 kinds of Twitter networks

27. [Divided]
Polarized Crowds
[Unified]
Tight Crowd
[Fragmented]
Brand Clusters
[Clustered]
Community Clusters
[In-Hub & Spoke]
Broadcast Network
[Out-Hub & Spoke]
Support Network
6 kinds of Twitter networks

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How Can You Use This?
• You can use social network analysis to
identify influencers and people who are
interested in a particular topic and you can
examine the content they share.
• You can identify clusters of users interested in
a particular topic and use automated methods
to target them.

29. Betweenness Centrality
From Richard Ingram’s blog post visualising
Data: Seeing is Believing
http://www.richardingram.co.uk/2012/12/visu
alising-data-seeing-is-believing/

30. Degree Centrality
From Richard Ingram’s blog post visualising
Data: Seeing is Believing
http://www.richardingram.co.uk/2012/12/visu
alising-data-seeing-is-believing/

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Theresa May (29th May)

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Chorus Analytics Tweetcatcher
Desktop Edition
• Chorus-TCD is a product of Brunel University
which allows you to retrieve and analyse data.
• Uses Twitter’s Search API.
• Great video introduction here.

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Chorus
• This is the layout of Chorus Tweet Catcher

34. Chorus
• This is the layout of Chorus Tweet Vis
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35. Chorus Tutorials
• Chorus manual here
• Great video overview of Chorus here
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Mozdeh
• Mozdeh is a product of the ‘Statistical
Cybermetrics Research Group’ at the University
of Wolverhampton.
• Mozdeh is a Windows desktop program that can
gather tweets by automatically searching for
keywords associated with a topic.

37. Mozdeh
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• An example time series graph of 5,055,299
tweets related to norovirus

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Time Series Graphs

39. Mozdeh Tutorials
• Great user guide here
• Great theoretical overview here
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TAGS – Twitter Archiving
Google Sheets
• TAGS is a free Google Sheet template which
lets you setup and run automated collection
of search results from Twitter.
• Set up TAGS here https://tags.hawksey.info/get-
tags/

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TAGS – Twitter Archiving
Google Sheet

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COSMOS Project
• The Collaborative Online Social Media
Observatory (COSMOS): Social Media and Data
Mining is an ESRC project a part of the strategic
Big Data investment.
• The COSMOS Project (Burnap et al, 2014) uses
the Streaming API

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COSMOS Project
• Some of the features include generating:
• Word Clouds
• Frequency Charts
• Network Graphs
• Geographical Maps of Tweets

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COSMOS Project Layout

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COSMOS Tutorials
• Great video tutorial(s) here

47. NVivo
• You can import social media data captured
elsewhere into NVivo
• Or you can use Ncapture within NVivo to
pull in data
• Useful for content analysis and thematic
analysis
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48. Summary
• This presentation has provided an
overview of some free and paid tools that
can be used to capture and analyse
Twitter data
• Different tools allow you to perform
different types of analysis
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Prices
• Mozdeh, TAGS, COSMOS, and Chorus
are FREE
• DiscoverText (Professional) $49 a month
for academics and $24 a month for
students
• NodeXL Pro $199 a year for academics
and $29 a year for students

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Summer School
• 3-day intensive Summer School on social
media analytics taking place in Sibenik,
Croatia .June 28th to June 30th 2017
• More information here:
https://event.gg/5776/

51. iConference 2018 in Sheffield
• The theme of iConference 2018, Transforming
Digital Worlds, will be the importance of the
information field in transforming the increasingly
data-driven world.
• Run by a consortium of Information Schools
dedicated to advancing the information field
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52. Questions?
• Tweet me! @was3210
• Questions related to the tools?
• TAGS = @mhawksey
• NodeXL = @marc_smith
• COSMOS = @pbFeed
• Mozdeh = @mikethelwall
• DiscoverText = @StuartWShulman
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53. To
Discover
And
Understand.