An analysis of the KOT(Kenyans on Twitter) with regards to The Presidential Election of 2013.

1. The
KENYA
TWITTELECTIONS
2013
@SamerCostello @KevinMadung
AN ANALYSIS OF THE ELECTIONS ON #KOT
© Odipo Dev Visuals
Sunday, March 10, 13

2. The Kenyan elections took place on 4th March.
The tallying went on until the 8th
...and Uhuru Kenyatta declared as the winner on the
9th of March, 2013
This is an analysis of data within that time period.
Sunday, March 10, 13

3. The Facts
• Total Registered • Uhuru Kenyatta Votes
Voters : 14.3million 50.07% i.e 6,173,545
• Total Votes Cast : • Raila Odinga Votes
12.3million 43.3% i.e 5,340,546
UHURU
KENYATTA
Winner of
Presidential
Elections 2013
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4. Results by Constituency
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5. The 290 Constituencies
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6. The Battle of Numbers
The battle was based on
the number of votes
each candidate had in
their stronghold
constituencies
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7. RAILA’S VOTE DISTRIBUTION
The size is representative of voters garnered by
Raila Odinga in the constituency.
The color intensity is representative of the
NB: Some constituency data was not
number of voters in the constituency.
yet available at time of analysis
Sunday, March 10, 13

8. UHURU’S VOTE DISTRIBUTION
The size is representative of voters garnered by
Uhuru Kenyatta in the constituency.
The color intensity is representative of the
NB: Some constituency data was not
number of voters in the constituency.
yet available at time of analysis
Sunday, March 10, 13

9. During the election
period...the KOT(Kenyan’s on
twitter) all over the world
were actively letting their
thoughts on the process be
known
The data that follows is set between
22/02/1013 and 9/03/2013
Sunday, March 10, 13

10. Worldwide KOT Tweet-tivity Levels
NB: Based on popular hashtags during the period
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11. KOT Activity Distribution
The KOT were active from all
over the world.
These charts show the
activity levels distributions
from different parts of the
globe.
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12. Activity Levels VS Twitters
It was interesting to note that about 1/3 of the tweets on
the elections came from KOT in the USA.
This was however, not as a result of having most of the
KOT there(which is most likely not the case),
but because of the high activity levels of the twitter
populace there.
The same is likely to be the case in the distribution of
tweets in within the country.
The disparity in number of twitters is not proportional to
the difference in tweet levels shown in the charts.
Sunday, March 10, 13

13. TOP
KOT
TWEETS
United Kingdom United States of
America
It was noted that even though the USA
had a more prominent influence on the
ranking of the tweets worldwide(as
witnessed by the reappearance of USA
top tweets in the worldwide list) the
local tweets were the most dominant.
Worldwide
Sunday, March 10, 13

14. Could an accurate prediction have been made
based on twitter data?
Uhuru had more conversations about him during the above period, with the peak time emerging on
the night his victory became evident
The spike on 11th and 25th was as a result of the Presidential Debates held by the two media houses
on those nights, with hashtags #Debate2013 and #KEPresidentialDebate being on the spotlight.
Uhuru’s twitter prominence was averagely the same over both debates, but Raila’s had diminished on
the second one.
This was likely caused by the discussion of the ICC issue during the second debate.
Sunday, March 10, 13

15. Presidential Candidate’s Sentiment Analysis
Contrary to expectations, Uhuru’s tweets had a more positive sentiment to them than Raila’s.
Factors that may have influenced this include:
• Positive sentiment as a result of • Most of the tweets against
Uhuru winning the election Uhuru were written in humor
and sarcasm which the computer
• Negative sentiment by Raila’s interprets as positive sentiment
voters after due to trailing and
eventually losing the race • Tweets including Uhuru in them
as regards to maintaining peace,
• Uhuru’s positive online campaign in the event that he won, were
taken to be positive
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16. Most-Influential Tweeps
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17. Most-Influential Tweeps
The list contains the 9 most influential twitter handles that
tweeted about the Kenyan elections between 22nd
February and 9th March 2013.
The influence of these handles is not based on the tweets
during this period, but is instead a characteristic built over
an undetermined amount of time.
Tweets and Retweets however are in relation only to
Election content over the aforementioned period.
It is visible then, that different parties were actively
tweeting about the election...including observers,
prominent media personalities and individuals.
Sunday, March 10, 13

18. Twitter Peace Activists
Sunday, March 10, 13

19. Twitter Peace Activists
During the period, a massive amount of tweets encouraged peace
since Kenyans didn’t want a repeat of the bloodshed that
occurred after the 2007 elections.
The handles shown are those that actively tweeted the most with
respect to peace, and encouraged unity during the election period.
Common hashtags used by the tweeps to preach peace
included:
• KenyaKwanza • iPreachPeace
• Choice2013 • KenyaMoja
• Decision2013 • HakunaMatata
• KenyaDecides • Peace
Sunday, March 10, 13

20. The HashTags
Analyzing the top 3 handles, we notice that each of them adopted
a hashtag to use in their quests to spread peace through the KOT:
Julie Gichuru used #KenyaKwanza,
Larry Madowo used #Decision2013,
and Robert Alai used #Choice2013.
Sunday, March 10, 13

21. Overall Twitter Analysis
A representation of the traffic generated by the handles and their respective hashtags
over the past month.
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22. It was noted that the hashtags peaked at different days of the period
depending on what they were used to communicate and when they
were adopted.
For example, Julie’s #kenyakwanza peaked during the elections while
the rest peaked during the tallying period.
The sentiments associated with the hashtags also varied according
to the flexibility of the hashtag.
Sunday, March 10, 13

23. Associated Media
The images depict top pictures and videos associated with the
hashtags.
It was concluded that live streams garnered highest momentum as
the content was not constant in nature.
Pictures on the other hand varied depending on the message they
spread, with the fourth one above coming from an OLX ad.
Sunday, March 10, 13

24. Julie Gichuru and #KenyaKwanza
The graph shows exposure levels.
It can be seen that the hashtag’s exposure surpasses Julie’s after some time.
This can be attributed to adoption of the hashtag by other individuals.
Sunday, March 10, 13

25. Larry Madowo and #Decision2013
The graph shows exposure levels.
It can be seen that the hashtag’s exposure surpasses Larry’s after some time...but not by much.
This can be attributed to adoption of the hashtag by other individuals despite it’s constant use by Larry.
Sunday, March 10, 13

26. Robert Alai and #Choice2013
The graph shows exposure levels.
It can be seen that the hashtag’s exposure surpasses Robert’s after some time by a huge gap.
This can be attributed to adoption of the hashtag by other individuals and it’s high adaptability.
Sunday, March 10, 13

27. Sentiment Analysis
It can be seen that, despite the variation in positive and
negative use of the hashtags, all of them were positive
towards the announcement of the results, explaining the
relative peace in the country.
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28. Sentiment Analysis
Sentiment Graph
It is visible through the
graph and the top two
negative media associated
with the hashtags, that the
sentiments of KOT
improved towards and after
the announcement of the
presidentialresults
Negative Pics
Sunday, March 10, 13

29. THANK YOU FOR
WATCHING
@SamerCostello @KevinMadung
AN ANALYSIS OF THE ELECTIONS ON #KOT
© Odipo Dev Visuals
Sunday, March 10, 13