Using network science the understand elections: the South African 2014 national elections on Twitter

Kyle Findlay & Ockert Janse van RensburgUsing Network Science to Understand Elections: The 2014 South African National Elections on Twitter

Using Network Science to Understand Elections:The 2014 South African National Elections on Twitter

Kyle Findlay & Ockert Janse van Rensburg

Winner of the Gold Award for Best Paper at the 2015 Southern African Marketing Research Association (SAMRA) annual conference


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Let’s start by having a look at the data in action…

(video animation on next slide)


In the interest of privacy, we do not report on all influencers in this paper. We stick to only reporting those that already have a significant public presence, either in the South African media (e.g. politicians) or on Twitter itself (i.e. more than 10,000 followers).

This data is from Q2 2014. A lot can change in a year, including people’s opinions and political allegiances. Again, community membership should not be taken alone as proof of political views nor allegiances.

A few important caveats before we begin…

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This paper uses network theory-based approaches to identify communities of Twitter users within the data. It is important that readers understand that community membership does not 100% identify nor guarantee a user’s political views nor alignment. There are two main reasons for this:

1. Community membership is based on a non-deterministic algorithm that uses a random seed to start the community detection process. This means that community membership can be unstable and so reported memberships should be taken with a pinch of salt.

2. In simplistic terms, users are grouped into communities based on who they interact with most. Generally speaking, people tend to interact with other like-minded people; however, antagonistic interactions can also bind communities i.e. people may form part of the same community due to debates wherein users engage each other on their differing viewpoints.

Community membership

Privacy Time period


Contents

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1. So what were the conclusions?

2. Why focus on Twitter?

3. How did we analyse the data?

4. Party momentum

5. Overall election influencers & top content

6. The SA elections 2014 conversation map

7. Democratic Alliance (DA) community

8. Economic Freedom Fighters (EFF) community

9. Disenchanted ANC (ANC) community

10.ANC Stalwarts (ANC) community

So what were the conclusions?

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President Jacob Zuma has split the ANC in two

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Many supporters happily engage with official party mouthpieces such as @MyANC_, Sports Minister Fikile Mbalula and @ANC_Youth.

However, many disenchanted millennials appear to have found their thoughts echoed by unofficial influencers such as Khaya Dlanga, @Mtshwete and @TaxiDriverSipho

Support for the ANC is unequivocal amongst these groups but half of the party’s supporters do so despite of their dissatisfaction with Jacob Zuma


The 2014 national elections conversation on Twitter consisted of four main constituencies

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DA DA

EFF EFF

Dis-enchanted

ANC

Dis-enchanted

ANC

ANCstalwarts

ANCstalwarts

…which encompassed 52% of all users in the conversation

…and generated 85% of all tweets!


EFF community

@City_Press

@POWER987News

@SABCNewsOnline

@SAfmnews

@Radio702

ANC stalwarts

@ANN7tv

@The_New_Age

@SAgovnews

Some news media outlets’ content resonated primarily with specific constituencies

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DA community

@RSApolitics

@JacaNews

@BDliveSA

@dailymaverick

Disenchanted ANC

[No news entity appeared to cater specifically to, nor particularly resonated with, this community]

Many news outlets formed their own independent communities. For example…

• eNCA

• EWN News

• Mail & Guardian

• News24

• Times Live

• SA Breaking News

However, these news outlets’ content primarily resonated within the following communities:


The distribution of Twitter mentions gives us tantalising clues at possible future party momentum

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62%

22%

6%3% 2% 1% 1% 1% 1% 1% 1% 0% 0%

55%

22%

14%

1% 0% 1% 1% 2%4%

ANC DA EFF IFP NFP FF+ UDM ACDP AIC COPE Agang APC PAC

Seats in parliament % Twitter mentions

If the entire country was on Twitter, would the election results have looked like this?

Why focus on Twitter?

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Only 13% of South Africans belong to Twitter

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100%

46% 42%

13% 10% 7% 2%

Total consumermarket

Total socialnetworking

users

Facebook Twitter Google+ YouTube Instagram

% belong to

Source: TNS Sunday Times Top Brands Survey 2014


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“BuzzFeed found that

Twitter has a big cascade effect on other social media platforms.

Put simply, it appears that

huge stories often start as tweets,

then get shared by influencers to Facebook and other networks, where the original piece of content subsequently gets far more distribution.”

…however, Twitter has an outsized effect on information spread

Source: http://www.fastcompany.com/3043788/sxsw/twitters-influence-problem-visualized

How did we analyse the data?

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user location

1,461,909(3 March – 12 May 2014)

user time-zoneuser languagetweet language

We started with 1.5m tweets about the elections which we cleaned extensively to remove irrelevant tweets…


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981,878tweets in the end

irrelevant hashtagsirrelevant influencersirrelevant retweetsk-means clusteringconversation network


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We connected users that interacted with each other


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…and then ran a community detection algorithm to identify distinct communities


We ‘clustered’ tweets into topics using Latent DirichletAllocation (LDA)

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Party momentum

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21

248

89

25

10 6 4 4 3 3 3 2 1 1


Seats in parliament

A reminder of the actual election results…*

* …which follow a power law (R² = 0.97)


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62%

22%

6%

3% 2% 1% 1% 1% 1% 1% 1% 0% 0%

38%

25%

13%

3% 2% 1% 1% 1% 0%

4% 3%0% 1%


% of seats in parliament % of media coverage

R=0.95

Party media coverage aligned fairly closely with the actual results

Source: Media Monitoring Africa Election Coverage 2014, http://elections2014.mediamonitoringafrica.org


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62%

22%

6%

3% 2% 1% 1% 1% 1% 1% 1% 0% 0%

55%

22%

14%

1% 0% 1% 1% 2%4%


% of seats in parliament % Twitter mentions

R=0.99

…but each party’s share of Twitter mentions aligned even better with their actual results


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Twitter share of mentions notably diverged from actual seats in parliament in two cases…

The ANC received less than its fair share of Twitter mentions than we would expect given its final number of parliamentary seats won

The EFF received more Twitter mentions that seats won The DA received

exactly its fair share of mentions versus seats won


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The results might imply that, if South African Twitter users were more representative of the voting public,…

…the ANC might have received far fewerseats (62% vs. 55%)

…and most of these losses might have come from the EFF which might have received a greatershare of seats (6% vs. 15%)

…while the DA’s voter block probably is more representative of its Twitter users, thus its share of seats neatly aligns with its share of Twitter mentions (22%)

What might these results imply (with a very healthy dose of speculation)?

However, it’s important to remember that this interpretation is

very speculative at best!


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The scientific debate on the predictability of Twitter mentions vs. elections is still undecided though…

Source: Young-Ho, E, et al. (2015). Twitter-based analysis of the dynamics of collective attention to political parties


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“Despite the many efforts, results are still inconclusive...”

“We conclude that the tweet volume is a good indicator of parties' success in the elections when considered over an optimal time window.”

Source: Young-Ho, E, et al. (2015). Twitter-based analysis of the dynamics of collective attention to political parties

Overall election influencers & top content

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39 008

34 592

31 481

27 746

12 855

12 764

10 478

10 051

9 602

8 085

7 671

7 629

6 649

6 379

6 364

6 050

5 092

5 031

4 735

4 639

@HelenZille

@MyANC_

@DA_News

@EconfreedomZA

@ANC_Youth

@Julius_S_Malema

@Maimanea

@MbalulaFikile

@AgangSA

@eNCANews

@News24

@LindiMazibuko

@City_Press

@SABreakingNews

@POWER987News

@Sentletse

@EWNReporter

@ChesterMissing

@SAPresident

@TimesLive

Top 20 influencers shown where influence = # interactions (retweets + mentions)


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@HelenZille

@MyANC_

@DA_News

@EconfreedomZA

@ANC_Youth

@Julius_S_Malema

@Maimanea

@MbalulaFikile

@AgangSA

@eNCANews

@News24

@LindiMazibuko

@City_Press

@SABreakingNews

@POWER987News

@Sentletse

@EWNReporter

@ChesterMissing

@SAPresident

@TimesLive

Democratic Alliance

African National Congress

Economic Freedom Fighters

News media

Top 20 influencers shown where influence = # interactions (retweets + mentions)


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10

6

18 15

21

20

16

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The top hashtags give us some insight into the most prevalent topics (see hashtags highlighted with arrows)

Top 30 hashtags. Excludes “elections”- and “South Africa”-related hashtagsNumbers inside arrows represent rank of hashtag in term of frequency of occurrence in data


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What was the top 20 most retweeted content?


Author Retweet content # retweets

@justicemalalaMbeki's #ANC in 99: 66.35% Mbeki's ANC 2004: 69.6% Zuma's ANC 2009: 65.9% Zuma's ANC 2014: 62.84

(22.12/08 May) #justsay…705

@TrevornoahJacob Zuma is a great. I bet he did this Nkandla thing just to unite all South Africans in a common anger at

corruption.590

@ProudlySACongratulations to Deputy President Motlanthe & his beautiful bride, Gugu on their wedding today!! @PresidencyZA

http://t.co…524

@IECSouthAfricaNational Assembly seats: APC–1; PAC–1; AGANG SA–2; ACDP–3; AIC–3; COPE –3; UDM–4; VF Plus–4; NFP–6;

IFP–10; EFF–25; DA–…490

@helenzilleBy saying that "only clever people" have problems with R246-mill Nkandla upgrade, Pres Zuma is implying that

ANC voters are…394

@[] @IECSouthAfrica apparently found in home of ANC party agent. https://t.co/OyoYIvI79Y 346

@alexeliseevZuma on #Nkandla: "It's not an issue with voters. It's an issue with bright people. Very clever people". What is he

saying…344

@Sentletse The ANC and the IEC must be ashamed of themselves! http://t.co/STwypvLg8M 342

@IECSouthAfrica I.E.C voting material found at a house of an anc party agent in ward 77 http://t.co/48MAjhqqXE" 326

@[]EFF votes found dumped near Diepsloot cc @Julius_S_Malema @Sentletse @EconFreedomZA with @IECSouthAfrica

stamp http://t.co/mIzvrow…325

@Julius_S_Malema We will soon announce the date of the march to the union buildings to demand Zuma's resignation as the president 294

@helenzilleMonitor the polls!! "@E_van_Zyl_17: "@JohnBiskado: IEC voting material found at house of anc party agent ward

77 http://t.…289

@MbalulaFikile But you cant use the same BIS bought with NSFAS to tweet "ANC HAS DONE NOTHING". Uxokelani? 280

@GarethCliff Oh no! RT @DonnyDunn: @GarethCliff @KienoKammies IEC integrity obliterated! http://t.co/wILOizXGXm 279

@MbalulaFikile Biggest loser of the century DR Mamphela Ramphela ,u Luzile shameeee 272

@TannieEvitaConfusius say: "He who knows nothing about his own house, knows even less about his own country."

@SAPresident271

@GarethCliffWho told @helenzille it would be a good idea to do this? Will she campaign in blackface next?

http://t.co/TzbwsqgHGL258

@GarethCliffEven if you didn't vote ANC, they will form your new govt. wishing them luck is wishing the best for all of us. Good

luck …268

@MaxduPreezDefend this, ANC: Public Works Dept redirected service delivery funds to pay for Nkandla in contravention of

constitution245

@MbalulaFikileYet you're on Twitter and can write that in perfect English, let's face it, you're ANC's good story. @lusylooya: ANC

ha…238


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And if we group the retweets by theme?


Ballot tampering

Nkandla

Political smack talkFikile Mbalula and the ANC’s ‘good story’

Election results & well wishingDeputy President Motlanthe‘s wedding

Malema march for Zuma’s resignation


Many of the top most shared images related to alleged ballot tampering

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This image drawing a parallel between President Jacob Zuma’s Nkandla scandal to e-tolling was one of the most popular


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…as was this image critical of DA leader, Helen Zille

The SA elections 2014 conversation map

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The overall elections conversation map

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The various regions of colour clearly highlight distinct communities in the elections conversation.

Specific influential accounts that led the conversation are clearly visible within each community, hinting at the agenda of each.


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Black influencers

?

EFF

DA(and FF+)

ANC

eNCA & EWN News

International news media

Gareth Cliff & Ulrich J van Vuuren

Comedians

Agang

News24 & TimesLive

SA Breaking News

IEC & PresidencyZA

Mail & Guardian

DJ Sbu

The top four communities encompass 52% of unique users and appear to relate to political parties. Other communities relate to news entities, DJs, comedians, etc.


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Black influencers

?

EFF

DA(and FF+)

ANC

However, the top four communities generated almost all of the tweets about the elections (85%)!


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It was not initially clear what the “black influencers” community stood for. It required some digging into their actual tweet topics to find out more…

Black influencers

???


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…so let’s unpack the top four communities in more detail…

Democratic Alliance (DA) community

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Mabine Seabe II@Mabine_Seabe

Lindiwe Mazibuko@LindiMazibuko

Helen Zille@helenzille

Democratic Alliance@DA_News

Mmusi Maimane@MaimaneAM*

RSApolitics@RSApolitics

Jacaranda News@JacaNews

ToxiNews@toxinews

Gavin Davis@gavdavis

Influencers

Top influencers ranked on # interactions (retweets + mentions). * Username has changed subsequently. Original account hacked?


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BDlive@BDliveSA

RSApolitics@RSApolitics

Jacaranda News@JacaNews

ToxiNews@toxinews

Daily Maverick@dailymaverick

Particularly resonant media entities

These news media accounts’ content resonated with this community more than any other (most mentions and retweets)


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Nkandla & Zuma corruption

Ballot tampering

Zille pro (e.g. made the party)

Zille against (e.g. Twitter meltdown)

Mazibuko for president

Maimane for president

ANC “good story” (sarcastic)

Topics of conversation

Summary based on top retweeted content and LDA topic models


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Top shared media


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Top shared media

Economic Freedom Fighters (EFF) community

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Redi Tlhabi@RediTlhabi

POWER987 News@POWER987News

EFF Official Account@EconFreedomZA

Julius Sello Malema@Julius_S_Malema

City Press Online@City_Press

Sentletse@Sentletse

SABC News Online@SABCNewsOnline

Ranjeni Munusamy@RanjeniM

Carien du Plessis@carienduplessis

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Influencers

Top influencers ranked on # interactions (retweets + mentions).


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SAfm news@SAfmnews

702@Radio702

City Press Online@City_Press

POWER987 News@POWER987News

SABC News Online@SABCNewsOnline




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Ballot tampering

March for Zuma’s resignation

ANC decline under Zuma

ANC’s “good story” (sarcastic)

Armed Bekkersdal ANC supporter




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Top shared media


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Top shared media

Black influencers (???) community

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Trev@Tokyo_Trev

Siya@Siya_THATguy*

Khaya Dlanga@khayadlanga

Mayihlome@MTshwete

IG: TaxiDriverSipho@TaxiDriverSipho

Nzinga@NzingaQ

I.G: Questionnier@Questionnier

L’Vovo Derrango@LvovoSA

DJ Lulo Cafe@LuloCafe

Influencers

Top influencers ranked on # interactions (retweets + mentions). NOTE: some users with <10k followers not shown for privacy reasons* Username has changed subsequently. Original account hacked?


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N/A

No media entities resonated primarily with just this community


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Long live the ANC

ANC’s good story

ANC’s decline under Zuma

No respect for Zuma

Voting ANC (some voting DA)

Congrats to Lindiwe Mazibuko

Zille ‘trying too hard’

Exasperation with EFF (and some support)

When we unpacked their topics of conversation, it became clear what defined them – their disappointment in Jacob Zuma!



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Top shared media

African National Congress (ANC) community

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ANN7 24-hour news@ANN7tv

Malusi Gigaba@mgigaba

ANC Info Feed@MyANC_

ANC Youth League@ANC_Youth*

Fikile Mbalula@MbalulaFikile

ANC-HISTORY@ANC_LECTURES

Vote @MyANC_!!!!!@anccadres

ANC Gauteng@GautengANC

The New Age@The_New_Age

Influencers

Top influencers ranked on # interactions (retweets + mentions). NOTE: some users with <10k followers not shown for privacy reasons* Username has changed subsequently. Original account hacked?


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ANN7 24-hour news@ANN7tv

The New Age@The_New_Age

SA Gov News@SAgovnews




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Love ANC

Love Zuma

ANC’s “good story”




66Summary based on top retweeted content and topic models

No specific media was particularly popular within this community within our data


Thank you

Documents

Using network science the understand elections: the South African 2014 national elections on Twitter