Trump vs. HillaryAnalyzing Viral Tweets during US Presidential Elections 2016

Walid Magdy1 and Kareem Darwish2

1School of Informatics, The University of Edinburgh, UK2Qatar Computing Research Institute, HBKU, Doha, Qatar

Email: wmagdy@inf.ed.ac.uk, kdarwish@qf.org.qaTwitter: @walid magdy, kareem2darwish

Abstract

In this paper, we provide a quantitative and qual-itative analyses of the viral tweets related to theUS presidential election. In our study, we focuson analyzing the most retweeted 50 tweets foreveryday during September and October 2016.The resulting set is composed 3,050 viral tweets,and they were retweeted over 20.5 million times.We manually annotated the tweets as favorableof Trump, Clinton, or neither. Our quantitativestudy shows that tweets favoring Trump were usu-ally retweeted more than pro-Clinton tweets, withthe exception of a few days in September and twodays in October, especially the day following thefirst presidential debate and following the releaseof the Access Hollywood tape. On two days in Oc-tober 2016, pro-Trump tweet volume accountedfor than 90% of the total tweet volume.

IntroductionSocial media is an important platform for politicaldiscourse and political campaigns (Shirky 2011; West2013). Political candidates have been increasingly us-ing social media platforms to promote themselves andtheir policies and to attack their opponents and theirpolicies. Consequently, some political campaigns havetheir own social media advisers and strategists, whosesuccess can be pivotal to the success of the campaign asa whole. In the context of this paper, we are interestedin measuring the volume and diversity of support for thetwo main candidates for the 2016 US presidential elec-tions, Donald Trump and Hillary Clinton, on Twitterduring the two months preceding the elections, namelySeptember and October 2016. The work is based on thedata being collected via TweetElect.com, which isan online website that tracks tweets and Twitter trendspertaining to the US presidential elections.

For our analysis, we use the top 50 retweeted tweets,aka viral tweets, for everyday in September and Oc-tober 2016 pertaining to the US presidential election.The total number of unique tweets that we analyze is3,050, whose retweet volume of 20.5 million retweets ac-counts for more than 50% of the total retweet volume

Copyright c© 2016, All rights reserved.

during these two months on TweetElect. After manu-ally tagging all the tweets in our collection for supportfor either candidate, we looked at: which candidate hasmore traction on Twitter and a more diverse supportbase; when a shift in the volume of supporting tweetshappens; and which tweets were the most viral.

We observed that retweet volume of pro-Trumptweets dominated the retweet volume of pro-Clintontweets on most days during September 2016, and al-most all the days during October. A notable exceptionwas the day after the first presidential debate and theday after the leak of the Access Hollywood tape in whichTrump used lewd language.

Data Collection

In this section, we describe the collection of viral tweets.We initially give an introduction to TweetElect website,which is the source we used to identify the daily viraltweets. Later, we explain the data annotation processand give some statistics on the data collected.

TweetElect

TweetElect.com1 is a free website that aggregatesand shows the most retweeted tweets related to the2016 US presidential election. The website shows tweetsabout the elections in general, with the option of dis-playing tweets about each of the two main candidatesseparately. It offers search functionality with filters onmedia type (text, image, video, or links), while en-abling the display of search results related to each can-didate separately. TweetElect shows the most retweetedtweets, images, videos, and links in the last hour, 12hours, 1 day, or 2 days.

During September and October, the number of ag-gregated tweets per day (including retweets) related tothe US presidential elections typically ranged between300k and 600k. This number increased dramatically af-ter specific events or revelations, such as after the pres-idential debates, where the number of tweets exceeded4 million tweets.

1http://www.tweetelect.com/

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TweetElect is a special edition of Tweet-Mogaz2 (Magdy 2013), which is an Arabic newsportal that automatically generates news from tweets.It uses state-of-the-art adaptive filtering methods fordetecting relevant tweets on broad and dynamic topics,such as politics and elections (Magdy and Elsayed2016). TweetElect used an initial set of 38 keywordsrelated to the US elections for streaming relevanttweets. Consequently, adaptive filtering continuouslyenriches the set of keywords with additional terms thatemerge by time (Magdy and Elsayed 2016).

Tweet Collection

We were interested in analyzing the most “viral” tweetspertain to the US presidential elections. Therefore, weconstructed a set of the most retweeted 50 topicallyrelevant (as provided by TweetElect.com) tweetsfor everyday in September and October 2016. Thus,our collection contained 3,050 unique tweets that wereretweeted 20.5 million times. By month, September had1,500 unique tweets with a retweet count of 6.67 million,and October had 1,550 tweets with a retweet count of13.89 million. This volume of retweets represents morethan 50% of the total tweet volume collected by Tweet-Elect related to the US elections during September andOctober 2016.

In our analysis, we show statistics based on threetypes of viral tweets:

• Top50: The top 50 viral tweets per day.

• Top10: The top 10 viral tweets per day. Checkingonly the top 10 rather than 50 can give a better in-dicator of the direction of the trends on Twitter onthat day, and the top few retweeted tweets usuallydominate the retweet volume.

• Top10F: The top 10 viral tweets per day for thecandidates’ supporters (“Fans”) only and excludingtweets from the official accounts of the candidates.Since many of the top tweets are usually coming fromthe presidential candidates, this gives a depth on thesupport of the candidates by what their fans say.

The total number of retweets for the TOP 50, TOP10, and TOP 10 Fa n tweets per day are 6.67 million,3.49 million, and 1.75 million retweets respectively. Fig-ures 1 and 2 show the virality of the top tweets day-by-day during September and October 2016 respectively.As shown, the days with the largest number of retweetsfor the top N tweets were September 27 and October10, which are the days following the first and seconddebate between the candidates 3.

Tweet Labeling

We labeled the tweets on two stages, as we labeled theviral tweets of each month directly after the end of this

2http://www.tweetmogaz.com/3Tweets time stamp is based on GMT

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Number of retweets of the top N viral tweets on the US elections

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Figure 1: Total number of retweets of the Top50, Top10,and Top10F daily viral tweets relating to the US elec-tions during September 2016

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Figure 2: Total number of retweets of the Top50, Top10,and Top10F daily viral tweets relating to the US elec-tions during October 2016

month. Tweets were labeled as pro-Trump, pro-Clinton,or neither.

Out of the 1,500 tweets collected during September,636 were tweeted by either of the candidates’ officialaccounts. This number was 612 out of 1,550 for October.These tweets were automatically annotated to be in thefavor of the candidate who posted them. The remainingtweets were then posted to a crowd-sourcing platform4

to be manually annotated. Each tweet was annotatedby at least 3 annotators, and the majority voting istaken for selecting the final label. A golden control set of17 tweets was provided to control the annotators workquality.

We asked annotators to label each of the tweet withone of three labels: 1) In favor of Trump, 2) In favor ofClinton, 3) Neither of them.

Instruction were given to annotators as follows:

• Tweets in favor of a candidate can be:

1. Clearly showing support to the candidate

2. Giving positive facts about the candidate orhis/her campaign (for example showing thathe/she leads in polls)

3. Attacking the other candidate

4https://www.crowdflower.com/

4. Making fun (or sarcasm) of the other candidate orhis/her supporters.

• “Neither of them” tweets is selected if:

1. The tweet is reporting news about the elections ora presidential candidate with no clear bias to be infavor or against.

2. The tweet is attacking both candidates.

Annotators were instructed to check the tweet con-tent carefully including any images, videos, or externallinks to have an accurate annotation. In addition, weadvised them to check the profile of tweet authors tobetter understand their position towards the candidatesif needed.

The annotators inter-agreement was 90%, which isconsiderably high among three annotators for an an-notation task with three choices. This gives high confi-dence in the quality of annotation.

Results and Analysis

Figures 7 and 8 show the direction of support of theTop50, Top10, and Top10F viral tweets per day forSeptember and October respectively. As it is shown, thenumber of daily viral tweets in favor of Trump is usu-ally larger than that for Clinton. This observation doesnot change when considering the Top 50 or 10 tweets.Furthermore, when considering the top viral tweets bytheir fans (excluding the official accounts of the candi-dates), the gap between Trump and Clinton was evenlarger, where 57% and 65% of the Top10F tweets inSeptember and October respectively were in favor ofTrump, whereas it was only 27% and 19% in favor ofClinton respectively. Looking at the daily viral tweets,it is evident that for most days, Trump had more viraltweets supporting him than Clinton.

For September 2016, Trump led Clinton in the vol-ume of viral tweets everyday during the month save 6days, with the day following the debate (9/27) showingthe highest percentage and volume of tweets supportingClinton. We inspected the other 6 days and they cor-responded to: (September 12-13) Trump complainingabout how the debates would be moderated and ques-tions about Clinton’s health; (September 15-16) Trumpsaying that women are bad for business (Oppenheim2016) and disavowing the “birther” claims that Presi-dent Obama was not born in the US; and (September23-24) nothing noteworthy. Trump also led Clinton inthe number of unique viral tweets everyday except for5 days, namely the 2 days following the debate, and onSeptember 12, 13, and 16.

Also in September, Pro-Trump tweets surged to morethan 70% of the volume of retweets on 3 days, namelySeptember 4, 6, and 9. On September 4, news broke thatClinton mishandled classified material and Trump’stop tweet receiving 19.5k retweets which stated: “LyinHillary Clinton told the FBI that she did not know theC markings on documents stood for CLASSIFIED. Howcan this be happening?” . On the 6th, hacked Clinton

emails were made public with with Trump’s top tweeton the topic receiving more than 14k retweets. On the9th, Clinton stated that half of Trump supporters are a“basket of deplorables”.

For the month of October, pro-Clinton tweet volumeexceeded pro-Trump tweet volume on only two daysnamely Oct. 7 and Oct. 26. October 7 coincides withthe release of the Access Hollywood video of Trumpmaking lewd comments, and coincides with the daywhen pro-Clinton tweets received the largest portion ofretweet volume (58%). The top retweeted tweets favor-ing Clinton were not as much pro-Clinton as they wereanti-Trump. The most retweeted tweet belonged to JebBush, the former hopeful in the Republican presidentialprimaries, in which he condemned Trump’s comments.Though the tapes were described by some as an “Octo-ber surprise”, pro-Trump tweets constituted 35% of thetweet volume. On October 26, the user “Bailey Disler”was praising the person who destroyed Trump’s star onthe Walk of Fame. His tweet was retweeted more than124k times, which accounts for 6% of the volume forthat day.

Also in October, Pro-Trump retweet volume out-paced pro-Clinton volume for all other days. In fact,pro-Trump retweet volume accounted for more than75% of the volume on 13 day during the month. Asidefrom Oct. 29 when the Federal Bureau of Investigation(FBI) announced that they are investigating HillaryClinton over misuse of email and Oct. 11 when he at-tacked the leaders of the Republican Party, nothing outof the ordinary was happening any of the other days.The two most prominent sources of pro-Trump viraltweets were the official accounts of Trump and Wik-iLeaks.

Results in Figures 7 and 8 are based on the top Nunique tweets. When we take into consideration the realvolume these tweets represents, i.e. counting each tweetin the top 50 with its number of retweets, the results canbe seen in Figures 3 and 4 for the Top50 for Septemberand October respectively. The graphs still show thatTrump had a larger number of supporting viral tweetsfor most of the days. However, when Clinton gets moreviral tweets, some of the tweets may receive an enor-mous number of retweets, as is clear on September 15and 27 when there were large spikes in the favor of Clin-ton. The overall share of retweets volume during themonth continues to be in favor of Trump. Even withthe spikes in pro-Clinton retweets, 54% and 67% of theretweet volume for September and October respectivelywas for tweets supporting Trump, 39% and 25% werepro-Clinton, and the remaining 7% and 8% were unbi-ased news or against both candidates.

We also looked at the diversity of tweet authors, andfound that there was not only more retweets in sup-port of Trump, but also they were authored by morepeople. The viral tweets in support of Trump were au-thored by 196 and 198 users for September and Oc-

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Figure 3: Total number of retweets of the Top50 dailyviral tweets for each candidate during September 2016

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Figure 4: Total number of retweets of the Top50 dailyviral tweets for each candidate during October 2016

tober respectively compared to 135 and 110 users re-spectively for Clinton. Furthermore, for September, interms of the number of unique viral tweets the per-centage of viral tweets supporting Trump that were au-thored by his official account was 31% compared to 66%of pro-Clinton tweets that were authored by her officialaccount. The percentages for October were consistentwith 35% for Trump and 63% for Hillary. Figures 5 and6 show the volume of retweets per author in our set ofviral tweets and suggests that there is greater diversityof pro-Trump tweet authors. Conversely, we looked atthe 50 tweets with the most retweets over the entire twomonths of September and October that are supportingeither candidate. For September, 45 were authored bythe official Trump account (making up 92% of the vol-ume of the top 50 tweets) compared to 39 that were au-thored by the official Clinton account (making up 68%of the volume of the top 50 tweets). For October, 32were authored by the official Trump account (makingup 57% of the volume of the top 50 tweets) comparedto 23 that were authored by the official Clinton account(making up 39% of the volume of the top 50 tweets).The drop in percentages of top retweeted tweets beingauthored by the candidates from September to Octo-ber is notable and warrants more investigation. Table1 and 2 show the top 10 most retweeted Twitter ac-counts along with the number of tweets in our set and

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Figure 6: Total number of retweets per users whosetweets showed in the Top50 during October 2016

retweet volume 5. One interesting observation is thataccounts with some of the most retweeted pro-Clintontweets had only one tweet in our set and there was nocorrelation between tweet counts and retweet volume.For accounts with pro-Trump tweets, there is correla-tion between tweet count and retweet volume and 4 outof the top 10 accounts are affiliated with the Trumpcampaign in both months.

By volume, tweets from Trump’s official account ac-counted for 62% and 54% of pro-Trump retweets com-pared to 68% and 52% for Clinton in September andOctober respectively. In fact, Trump was more likely tobe retweeted than Clinton. In September, the averageretweet count for Trump was 8,434 compared to 5,140for Clinton. Similarly in October, Trump was retweeted13,471 time on average compared to 8,080 for Clinton.Figures 5 and 2 show the volume of retweets per au-thor for September and October respectively. Tables 3and 4 list the most retweeted tweets over the months ofSeptember and October respectively in support of both

5The number of retweets in Tables 1-4 are taken at thetime of the study. This number is expected to change overtime

candidates. Again, tweets by the official accounts of thecandidates dominate the top spots. Also, aside fromTrump’s tweet stating “Mexico will pay for the wall!”,none of the top tweets discuss policy, but are rather at-tacks against the other candidate or their supporters orself promotion.

LimitationsTo better understand the results presented here, thereare a few limitations that need to be considered:

1. The top 50 viral tweets do not have to be represen-tative of the whole collection. Nonetheless, they stillrepresents over 50% of the tweets volume on the USelections during the period of the study.

2. Results are based on tweets collected from Tweet-Elect. Although it is highly robust, the site uses au-tomatic filtering methods that are not perfect. There-fore, there might be other relevant viral tweets thatwere not captured by the filtering method.

3. Measuring support for a candidate using viral tweetsdoes not have to represent actual support on theground for many reasons. Some of these reasons in-clude the fact that demographics of Twitter usersmay not match the general public, more popular ac-counts have a better chance of having their tweets goviral, or either campaign may engage in astroturfing,in which dedicated groups may methodically tweet orretweet pro-candidate messages.

Conclusion and Future WorkIn this paper, we presented the top retweeted tweets(viral tweets) from September and October 2016 sup-porting the two main candidates for the 2016 US pres-

idential elections. We provided quantitative and qual-itative analysis of these top tweets. Our results showthat pro-Trump tweets were retweeted more often thanpro-Clinton tweets, and he had more support on mostdays, especially in October, few days before the electionday.

Further analysis is required to determine the leaningsof the authors of negative/positive tweets and the topicsof interest that they discussed. In addition, it is veryinteresting to study if these trends for both candidatesare natural, or if campaign are engaged in astroturfing,in which dedicated groups of people methodically tweetor retweet pro-candidate messages.

References[Magdy and Elsayed 2016] Magdy, W., and Elsayed, T.2016. Unsupervised adaptive microblog filtering forbroad dynamic topics. Information Processing & Man-agement 52(4):513–528.

[Magdy 2013] Magdy, W. 2013. Tweetmogaz: a newsportal of tweets. In Proceedings of the 36th internationalACM SIGIR conference on Research and developmentin information retrieval, 1095–1096. ACM.

[Oppenheim 2016] Oppenheim, M. 2016. Ivanka trumpcuts interview short after questions over father’s ’preg-nancy is inconvenient for business’ quote. Indepen-dent.co.uk.

[Shirky 2011] Shirky, C. 2011. The political power of so-cial media: Technology, the public sphere, and politicalchange. Foreign affairs 28–41.

[West 2013] West, D. M. 2013. Air wars: Television ad-vertising and social media in election campaigns, 1952-2012. Sage.

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Figure 7: The direction of support of the top viral tweets during September on the US presidential election 2016

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Figure 8: The direction of support of the top viral tweets during October on the US presidential election 2016

Table 1: Most retweeted accounts supporting the two candidates for Septemberpro-Clinton

Account Number of Tweets Retweet volume descriptionHillary Clinton 386 1,984,078 Official accountOzzyonc 1 152,756 Twitter userJerry Springer 1 150,872 Tabloid TV show presenterSenator Tim Kaine 8 31,769 Running mate official accountDaniel Dale 5 29,885 Canadian journalistDavid Fahrenthold 4 29,557 Washington Post reporterLittle Miss Flint 1 28,863 Civic activistBernie Sanders 5 28,513 Democratic presidential candidateJoe Biden 4 25,300 Vice presidentI’m 5’13 1 22,306 Twitter user

pro-TrumpAccount Number of Tweets Retweet volume descriptionDonald J. Trump 251 2,117,249 Official accountKellyanne Conway 48 106,796 Campaign strategistWikiLeaks 22 102,242 Site that released Clinton emailsDonald Trump Jr. 22 63,611 Trump’s sonPaul Joseph Watson 29 60,460 Right-leaning journalistDaniel Scavino Jr. 15 46,300 Campaign strategistMike Cernovich 25 37,317 Lawyer and authorDEPLORABLE TRUMPCAT 14 29,381 Twitter userFox News 14 28,706 Right-leaning mediaLou Dobbs 9 22,752 Fox News anchor

Table 2: Most retweeted accounts supporting the two candidates for Octoberpro-Clinton

Account Number of Tweets Retweet volume descriptionHillary Clinton 246 1987701 Official accountStephen King 2 135744 Famous authorBailey Disler 1 124322 Twitter userKat Combs 1 105118 Twitter userEs un racista 1 102063 Twitter userErin Ruberry 1 72167 Twitter userSenator Tim Kaine 12 68898 Running mate official accountRichard Hine 1 66817 Marketing executivebilly eichner 2 66761 Comedian and actorJeb Bush 1 64545 Republican politician

pro-TrumpAccount Number of Tweets Retweet volume descriptionDonald J. Trump 366 4930413 Official accountWikiLeaks 66 758814 Site that released Clinton emailsKellyanne Conway 60 271857 Campaign strategistOfficial Team Trump 30 233680 Trump campaingMike Pence 36 216982 Running mate official accountDan Scavino Jr. 45 200315 Campaign strategistPaul Joseph Watson 40 189277 Right leaning journalistJared Wyand 20 110943 Self proclaimed nationalistRob Fee 1 99401 ComedianDonald Trump Jr. 18 77036 Trump’s son

Table 3: Top retweeted tweets supporting each candidate for September 2016.Most retweeted pro-Clinton Tweets

Author Date Tweet CountOzzyonc 9/15 Donald Trump said pregnancy is very inconvenient for businesses like his mother’s

pregnancy hasn’t been inconvenient for the whole world.152,756

Jerry Springer 9/27 Hillary Clinton belongs in the White House. Donald Trump belongs on my show. 150,872Hillary Clinton 9/27 RT this if you re proud to be standing with Hillary tonight. #debatenight

https://t.co/91tBmKxVMs72,443

Hillary Clinton 9/27 I never said that. – Donald Trump who said that. #debatenighthttps://t.co/6T8qV2HCbL

72,111

Hillary Clinton 9/10 Except for African Americans Muslims Latinos immigrants women veterans – andany so-called losers or dummies. https://t.co/rbBg2rXZdm

50,913

Most retweeted pro-Trump TweetsAuthor Date Tweet CountDonald J. Trump 9/24 If dopey Mark Cuban of failed Benefactor fame wants to sit in the front row perhaps

I will put Gennifer Flowers right alongside of him! 30,950

Donald J. Trump 9/20 Hillary Clinton is taking the day off again she needs the rest. Sleep well Hillary -see you at the debate!

30,900

Donald J. Trump 9/01 Mexico will pay for the wall! 30,464Donald J. Trump 9/27 Nothing on emails. Nothing on the corrupt Clinton Foundation. And nothing on

#Benghazi. #Debates2016 #debatenight27,177

Donald J. Trump 9/10 While Hillary said horrible things about my supporters and while many of hersupporters will never vote for me I still respect them all!

25,882

Table 4: Top retweeted tweets supporting each candidate for October 2016.Most retweeted pro-Clinton Tweets

Author Date Tweet CountBailey Disler 10/26 Good morning everyone especially the person who destroyed Donald Trump’s walk

of fame star https://t.co/IcBthxMPd9124,322

Stephen King 10/21 My newest horror story: Once upon a time there was a man named Donald Trumpand he ran for president. Some people wanted him to win.

121,635

Kat Combs 10/10 Trump writing a term paper: Sources Cited: 1. You Know It 2. I know It 3. Every-body Knows It

105,118

Es un racista 10/08 Anna for you to sit here call Trump a racist is outrageous Anna: OH?! Well lemmedo it again in 2 languages! https://t.co/nq4DO7bN7J

102,063

Rob Fee 10/08 How are so many people JUST NOW offended by Trump? It s like getting to the7th Harry Potter book realizing Voldemort might be a bad guy.

99,401

Most retweeted pro-Trump TweetsAuthor Date Tweet CountDonald J. Trump 10/08 Here is my statement. https://t.co/WAZiGoQqMQ 52,887WikiLeaks 10/14 Democrats prepared fake Trump grope under the meeting table Craigslist employ-

ment advertisement in May 2016 https://t.co/JM9JMeLYet45,348

WikiLeaks 10/03 Hillary Clinton on Assange Can’t we just drone this guy – reporthttps://t.co/S7tPrl2QCZ https://t.co/qy2EQBa48y

45,233

Mike Pence 10/10 Congrats to my running mate @realDonaldTrump on a big debate win! Proud tostand with you as we #MAGA.

42,178

Donald J. Trump 10/08 The media and establishment want me out of the race so badly - I WILL NEVERDROP OUT OF THE RACE WILL NEVER LET MY SUPPORTERS DOWN!#MAGA

41,386