The document discusses tools used to analyze Twitter data around the #SocMedHe conference hashtag, including Brilliant Tags and NodeXL. Brilliant Tags was used to pull Twitter data into a spreadsheet and track hashtags over time. NodeXL produced a network graph of 146 Twitter users discussing the conference. The graph showed a tightly connected group sharing both within and outside the conference. In the future, the author wants to analyze geographic distributions and write a collaborative paper on insights from the network analysis.

1. #SOCMEDHE
MORE THAN A
CONFERENCE

2. QUICK
OVERVIEW
A short explanation of some of the
tools used,
followed by an explanation of some
of the measures used
graphically seeing the groupings.

3. BRILLIANT TAGS
Developed by Martin Hawksey Google Sheets based https://docs.google.com/spreadsheets/d/1S
23uOXD-
BaWX4MnShveTk3LY32II3p4wEZ4G4B-
h1fg/edit?usp=sharing

4. EXAMPLE

5. IS THERE A
GROUP IN THE
MIDDLE? –
JUST REPLIES

6. REPLIES, TWEETS, MENTIONS AND RETWEETS,

7. GETTING GOING
IS RELATIVELY
EASY
• Go to https://tags.hawksey.info/ create a new spreadsheet
via Get TAGS and select TAGS v6.1
• Make a copy
• In box 2 enter the search term e.g. #socmedhe21
• Use the TAGS pull down menu select run now!
• Whole load a authorization
• In TAGS menu update hourly
• Share button: so all can view it.
https://docs.google.com/spreadsheets/d/1o49hgPpud99Fd
VD-DxShD1B_v4fuPdTZoTdrVZFCjXI/edit?usp=sharing

8. NODEXL
Free and Pro/education paid version
Excel based
Produces pretty graphs
…and a load of hidden statistics

10. SO WHAT ELSE?
• The graph represents a network of 146 Twitter users whose recent tweets
contained "#SocMedHe20", or who were replied to or mentioned in those tweets,
taken from a data set limited to a maximum of 18,000 tweets. The network was
obtained from Twitter on Thursday, 17 December 2020 at 17:41 UTC.
The tweets in the network were tweeted over the 8-day, 4-hour, 37-minute period
from Wednesday, 09 December 2020 at 12:52 UTC to Thursday, 17 December
2020 at 17:29 UTC

11. • Vertices : 146
Unique Edges : 468
Edges With Duplicates : 3411
Total Edges : 3879
Number of Edge Types : 5
Mentions : 1484
MentionsInRetweet : 1187
Replies to : 474
Retweet : 592
Tweet : 142
Self-Loops : 145
Maximum Vertices in a Connected Component : 146
Maximum Edges in a Connected Component : 3879
Maximum Geodesic Distance (Diameter) : 5

12. LAST TOOL FOR
TODAY
Using the tweets in the large TAGS
file from the beginning wrote a bit of
code to do simple sentiment analysis
Are tweets positive, neutral or
negative?

14. MORE THAN A
CONFERENCE
• At the very least it is a very positive conference
• Graphs both in TAGS and NodeXL
• seems to show a tightly connected group that
shares inside and outside of the conference
• Also the mentions a lot of people outside the
conference group or is mentioned by people
outside of the main group.
• Over the time the TAGS plot was run there was
over 3000 tweets – most on the day.
• Conclusion: Too early to say

15. TYPE OF NETWORK
• Using Himelboim, I. et al. (2017)
classification on social network –
possibly ingroup is the best
match?
• The clusters that emerge in these
networks are highly intercon-
nected and essentially overlap
one another. High-density
networks enable shared
knowledge, interaction, and stabil-
ity

16. WHERE NEXT
Would like to have a collaborative
paper on this topic – new insights
Looking at declared geographic
distribution

17. SOURCES
• https://docs.google.com/spreadsheets/d/1S23uOXD-
BaWX4MnShveTk3LY32II3p4wEZ4G4B-h1fg/edit?usp=sharing
• https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=243574
• Himelboim, I. et al. (2017) ‘Classifying Twitter Topic-Networks Using Social Network
Analysis’, Social Media + Society. doi: 10.1177/2056305117691545.