Android vs iPhone: Trends in a Month’s Worth of Trumpian Tweetage

What’s in a month’s worth of presidential tweetage?

I prepared a dataset containing a total of 123 public Tweets and corresponding metadata from user_id_str 25073877 between 15 February 2017 06:40:32 and 15 March 2017  08:14:20 Eastern Time (this figure does not factor in any tweets the user may have deleted shortly after publication). Of the 123 Tweets 68 were published from Android; 55 from iPhone. The whole text of the Tweets in the dataset accounts for 2,288 words, or 12,364 characters (no spaces; including URLs).

Using the Trends tools from Voyant Tools by Stéfan Sinclair & Geoffrey Rockwell I visualised the raw frequencies of the terms ‘Android’ and ‘iPhone’ in this dataset over 30 segments (more or less corresponding to the length of the month covered in the dataset) where each timestamped Tweet, sorted in chronological order, had its corresponding source indicated.

The result looked like this:

Raw frequency of Tweets per source in 30 segments by realdonaldtrump between 15 February 2017 06:40:32 and 15 March 2017 08:14:20 Eastern Time. Total: 123 Tweets: 68 from Android; 55 from iPhone. Data collected and analysed by Ernesto Priego. CC-BY. Chart made with Trends, Voyant Tools by Stéfan Sinclair & Geoffrey Rockwell (CC 2017).
Raw frequency of Tweets per source in 30 segments by realdonaldtrump between 15 February 2017 06:40:32 and 15 March 2017 08:14:20 Eastern Time. Total: 123 Tweets: 68 from Android; 55 from iPhone. Data collected and analysed by Ernesto Priego. CC-BY. Chart made with Trends, Voyant Tools by Stéfan Sinclair & Geoffrey Rockwell (CC 2017).

The chart does indeed reflect the higher number of Tweets from Android, and it also shows how over the whole document both sources are, in spite of more frequent absences from Tweets from iPhone, present throughout. The question as usual is what does this tell us. Back in 9 August 2016 David Robinson published an insightful analysis where he concludes that “he [Trump] writes only the (angrier) Android half”. With the source data I have gathered so far it would be possible (given the time and right circumstances) to perform a content analysis of Tweets per source, in order to confirm or reject any potential corelations between types of Tweets (re: tone, function, sentiment, time of day) and source used to post them.

Eyeballing the data, specifically since Inauguration Day until the present, does not seem to provide unambiguous evidence that the Tweets are undoubtedly written by two different persons (or more). What it is factual is that the Tweets do come from different sources (see my previous post), but at the moment, like with everything else this administration has been doing, my cursory analysis has only found conflicting insights, where for example a Tweet one would perhaps have expected to have been posted from iPhone (attributable hypothetically to a potentially less inflammable aide) was in fact posted from Android, and viceversa.

I may be wrong, but at the moment I cannot see any evidence there is any kind of predictable pattern, let alone strategy, behind the alternation between Android and iPhone (the only two type of sources used to publish Tweet from the account in question in the last month). Most of the times Tweets by source type will come in sequences of four or more Tweets, but sometimes a random lone Tweet from a different source will be sandwiched in between.

More confunsigly, all of the Tweets published between 08/03/2017 18:50 and 15/03/2017  08:14:20 have only had iPhone as source, without exception. Attention to detail is required to run robust statistical and content analyses that consider complete timestamps and further code the Tweet text and time data into more discrete categories, attempting a high level of granularity at both the temporal (time of publishing; ongoing documented events) and textual (content; discourse) levels. (If you are reading this and would like to take a look at the dataset, DM me via Twitter).

Anyway. In case you are curious, here’s the top 20 most frequent words in the text of the tweets, per source, in this dataset ( 15 February 2017 06:40:32 and 15 March 2017  08:14:20 Eastern Time). Analysis courtesy of Voyant Tools, applying a customised English stop words list (excluding Twitter-specific terms like rt, t.co, https, etc, but leaving terms in hashtags).

Android iPhone
Term Count Trend Term Count Trend
fake 11 0.007795889 great 16 0.016129032
great 11 0.007795889 jobs 14 0.014112903
media 10 0.007087172 america 6 0.006048387
obama 10 0.007087172 trump 6 0.006048387
election 9 0.006378455 american 5 0.005040322
just 9 0.006378455 join 5 0.005040322
news 9 0.006378455 big 4 0.004032258
big 8 0.005669738 healthcare 4 0.004032258
failing 6 0.004252303 meeting 4 0.004032258
foxandfriends 6 0.004252303 obamacare 4 0.004032258
president 6 0.004252303 thank 4 0.004032258
russia 6 0.004252303 u.s 4 0.004032258
democrats 5 0.003543586 whitehouse 4 0.004032258
fbi 5 0.003543586 address 3 0.003024194
house 5 0.003543586 better 3 0.003024194
new 5 0.003543586 day 3 0.003024194
nytimes 5 0.003543586 exxonmobil 3 0.003024194
people 5 0.003543586 investment 3 0.003024194
white 5 0.003543586 just 3 0.003024194
american 4 0.002834869 make 3 0.003024194

Android vs iPhone: Most Frequent Words from_user_id_str 25073877 Per Source

I have archived 3,603 public Tweets from_user_id_str 25073877 published between 27/02/2016 00:06 and 27/02/2017 12:06 (GMT -5, Washington DC Time). This is almost exactly a year’s worth of Tweets from the account in question.

Eight source types were detected in the dataset. Most of the Tweets were published either from iPhone (46%) or an Android (45%).

The Tweet counts per source are as follows:

 

Instagram 2
MediaStudio 1
Periscope 1
Twitter Ads 1
Twitter for Android 1629
Twitter for iPad 22
Twitter for iPhone 1660
Twitter Web Client 287
 Total 3603

 

The table above visualised as a bar chart, just because:

 

Source of 3603 Tweets from_user_id_str 25073877 (27/02/2016 00:06 to 27/02/2017 12:06) Bar chart.

 

As a follow/up to a previous post, I share in the table below the top 50 most frequent word forms per source (iPhone and Android) in this set of 3,603 Tweets  from_user_id_str 25073877, courtesy of a quick text analysis (applying a customised English stop word list globally) made with Voyant Tools:

 

Android iPhone
Term Count Trend Term Count Trend
great 276 0.008124816 thank 417 0.015241785
hillary 252 0.00741831 trump2016 215 0.007858475
trump 184 0.005416544 great 190 0.006944698
crooked 162 0.004768914 makeamericagreatagain 165 0.006030922
people 160 0.004710038 join 160 0.005848167
just 151 0.004445099 rt 144 0.00526335
clinton 120 0.003532529 hillary 119 0.004349574
big 107 0.003149838 clinton 118 0.004313023
media 106 0.0031204 america 111 0.004057166
thank 94 0.002767148 trump 104 0.003801309
bad 89 0.002619959 make 89 0.003253043
president 88 0.002590521 new 88 0.003216492
make 86 0.002531646 tomorrow 82 0.002997186
america 85 0.002502208 people 75 0.002741328
cnn 85 0.002502208 maga 73 0.002668226
country 72 0.002119517 today 73 0.002668226
like 72 0.002119517 americafirst 69 0.002522022
u.s 72 0.002119517 draintheswamp 68 0.002485471
time 71 0.00209008 tonight 67 0.00244892
said 67 0.001972329 ohio 66 0.002412369
jobs 66 0.001942891 vote 63 0.002302716
vote 63 0.001854578 just 61 0.002229614
win 63 0.001854578 florida 59 0.002156512
new 62 0.00182514 crooked 52 0.001900654
going 59 0.001736827 going 49 0.001791001
news 58 0.001707389 imwithyou 49 0.001791001
bernie 56 0.001648513 president 49 0.001791001
foxnews 55 0.001619076 votetrump 49 0.001791001
good 54 0.001589638 tickets 46 0.001681348
wow 53 0.0015602 american 43 0.001571695
job 50 0.001471887 time 43 0.001571695
nytimes 50 0.001471887 pennsylvania 42 0.001535144
republican 50 0.001471887 poll 41 0.001498593
0 49 0.001442449 soon 41 0.001498593
today 49 0.001442449 support 41 0.001498593
totally 49 0.001442449 enjoy 38 0.00138894
enjoy 48 0.001413012 campaign 37 0.001352389
cruz 46 0.001354136 rally 37 0.001352389
election 46 0.001354136 carolina 35 0.001279287
look 46 0.001354136 north 35 0.001279287
want 46 0.001354136 live 34 0.001242735
obama 44 0.001295261 speech 33 0.001206184
dishonest 41 0.001206947 california 18 0.000657919
can’t 39 0.001148072 hillaryclinton 18 0.000657919
night 39 0.001148072 honor 18 0.000657919
really 39 0.001148072 job 18 0.000657919
show 39 0.001148072 nevada 18 0.000657919
way 39 0.001148072 right 18 0.000657919
ted 38 0.001118634 supertuesday 18 0.000657919

 

I thought you’d like to know.

Donald’s Followers Going Up and Up…

In the context of popular calls to unfollow it (there’s a hashtag too), I  thought it would be interesting to look at how the number of followers of said Twitter account has been changing recently.

I looked at a dataset of all the Tweets from the account linked above timestamped between 04/11/2016 14:56 and 13/02/2017 22:30 (Washington DC time).

The change in followers (user_followers_count) in that period of time looks like this:

user_follower_count growth from:realdonaldtrump in tweets timestamped between 04/11/2016 14:56 and 13/02/2017 22:30 (Washington DC time)

 

The world appears to be collapsing, but his follower count keep going up… I thought you’d like to know.

We’ll keep an eye on this.

If you want to be able to read the account’s tweets without following it directly, there are many options. In case it’s useful, here’s a live searchable archive of recent tweets. (It’s bandwidth and Tweet volume dependent, so the resource may not always load).

 

Words Donald Likes So Far!

Trump Simplest Words image Image via The Telegraph
Image via The Telegraph, 20 September 2016

Since 20/01/2017 07:31:53 AM Eastern Time until 06/02/2017  07:07:55 AM Eastern Time Donald has…

  • …published 106 Tweets with his realDonaldTrump Twitter account. (He has published at least two more in the time I’ve been drafting this).
  • In this collection only one was published from the Twitter Web Client (the first one in this set)
  • 34 Tweets were published from Twitter for iPhone (mostly for Tweets between 20/01/2017 23:56 and 02/02/2017  12:29:16)
  • the remaining 71 Tweets were published from Twitter for Android.
  • All his latest Tweets, between 03/02/2017  06:24:51 and 06/02/2017  07:07:55, were published from Twitter for Android.
  • In this corpus he typed about 2,096 words or word forms (including URLs, Twitter account mentions and hashtags). This is about 5 pages.
  • 67 of his 106 Tweets include exclamation marks (!).
  • 31 of this 106 Tweets have included at least one word in all caps.

Sorry for all the bold type above.

Finally, these are the top 50 most frequent words (and emojis) in this set of 106 realDonaldTrump Tweets, courtesy of a quick text analysis (applying a customised English stop word list globally) made with Voyant Tools:

Term Count Trend
people 19 0.008796296
country 13 0.006018519
great 12 0.005555556
u.s 10 0.00462963
america 9 0.004166667
news 9 0.004166667
bad 8 0.003703704
fake 8 0.003703704
security 7 0.003240741
american 6 0.002777778
court 6 0.002777778
decision 6 0.002777778
enjoy 6 0.002777778
jobs 6 0.002777778
judge 6 0.002777778
just 6 0.002777778
meeting 6 0.002777778
today 6 0.002777778
ban 5 0.002314815
going 5 0.002314815
iran 5 0.002314815
make 5 0.002314815
states 5 0.002314815
thank 5 0.002314815
tonight 5 0.002314815
beginning 4 0.001851852
big 4 0.001851852
bring 4 0.001851852
coming 4 0.001851852
day 4 0.001851852
deal 4 0.001851852
election 4 0.001851852
illegal 4 0.001851852
interview 4 0.001851852
interviewed 4 0.001851852
like 4 0.001851852
long 4 0.001851852
nytimes 4 0.001851852
obama 4 0.001851852
p.m 4 0.001851852
party 4 0.001851852
president 4 0.001851852
supreme 4 0.001851852
united 4 0.001851852
whitehouse 4 0.001851852
yesterday 4 0.001851852
ºðÿ 4 0.001851852
abc 3 0.001388889
administration 3 0.001388889

So these are the most frequent presidential words so far.

I thought you would like to know.