TheKENYA

TWITTELECTIONS2013

AN ANALYSIS OF THE ELECTIONS ON #KOT

@KevinMadung

© Odipo Dev Visuals

@SamerCostello

Sunday, March 10, 13

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.

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The Facts• Total Registered

Voters : 14.3million

• Total Votes Cast : 12.3million

• Uhuru Kenyatta Votes 50.07% i.e 6,173,545

• Raila Odinga Votes 43.3% i.e 5,340,546

UHURU KENYATTA

Winner of Presidential

Elections 2013

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Results by Constituency

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The 290 Constituencies

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The Battle of Numbers

The battle was based on the number of votes each candidate had in

their stronghold constituencies

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RAILA’S VOTE DISTRIBUTION

The size is representative of voters garnered by Raila Odinga in the constituency.

The color intensity is representative of the number of voters in the constituency.

NB: Some constituency data was not yet available at time of analysis

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UHURU’S VOTE DISTRIBUTION

The size is representative of voters garnered by Uhuru Kenyatta in the constituency.

The color intensity is representative of the number of voters in the constituency.

NB: Some constituency data was not yet available at time of analysis

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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

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Worldwide KOT Tweet-tivity Levels

NB: Based on popular hashtags during the periodSunday, March 10, 13

The KOT were active from all over the world.

These charts show the activity levels distributions from different parts of the

globe.

KOT Activity Distribution

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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.

Activity Levels VS Twitters

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TOP KOT

TWEETS

United Kingdom

Worldwide

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.

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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.

Could an accurate prediction have been made based on twitter data?

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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

Uhuru winning the election

• Negative sentiment by Raila’s voters after due to trailing and eventually losing the race

• Uhuru’s positive online campaign

• Most of the tweets against Uhuru were written in humor and sarcasm which the computer interprets as positive sentiment

• Tweets including Uhuru in them as regards to maintaining peace, in the event that he won, were taken to be positive

Presidential Candidate’s Sentiment Analysis

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Most-Influential Tweeps

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Most-Influential TweepsThe 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.

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Twitter Peace Activists

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Twitter Peace Activists

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

• Choice2013

• Decision2013

• KenyaDecides

• iPreachPeace

• KenyaMoja

• HakunaMatata

• Peace

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.

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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.

The HashTags

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Overall Twitter Analysis

A representation of the traffic generated by the handles and their respective hashtags over the past month.

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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.

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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.

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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.

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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.

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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.

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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.

Sentiment Analysis

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Sentiment Graph

Negative Pics

Sentiment Analysis

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

Sunday, March 10, 13

@SamerCostello

AN ANALYSIS OF THE ELECTIONS ON #KOT

@KevinMadung

© Odipo Dev Visuals

THANK YOU FOR WATCHING

Sunday, March 10, 13