THINKING BY NUMBERS Hello gopherterraneans! With that greeting I've bumped up my phlog vocabulary past the already heady (and very approximate) height of 18,769 words (and other word-mistakable strings). Yes rather than leave it to the next day, week, century, I got back from my evening run (great fun in the fog under a full moon, but pretty cold since it's winter and I run without clothes on) and decided to get stuck back into my statistical self-analysis begun at the end of my last post in response to the study of words different goups use frequently in Facebook posts (circa 2013) here: Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0073791 I only skimmed over the text, which does make some interesting additonal points, but the main product of the whole thing is definitely the world clouds for different sexes, ages, and personality types. The images of these are below, but beware huge 2-5MB image sizes: Words, phrases, and topics most highly distinguishing females and males https://journals.plos.org/plosone/article/figure/image?download&size=large&id=10.1371/journal.pone.0073791.g003 Words, phrases, and topics most distinguishing subjects aged 13 to 18, 19 to 22, 23 to 29, and 30 to 65 https://journals.plos.org/plosone/article/figure/image?download&size=large&id=10.1371/journal.pone.0073791.g004 Words, phrases, and topics most distinguishing extraversion from introversion and neuroticism from emotional stability https://journals.plos.org/plosone/article/figure/image?download&size=large&id=10.1371/journal.pone.0073791.g006 For internet data sippers like me, the PDF is only 2.5MB and has all those images too: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0073791&type=printable In terms of men and women, I'd say both groups look rather annoying, which is perhaps more validation of my choice to avoid Facebook. It was also clearly skewed towards American subjects. Since the study was done around when I was crossing over the 13-18 and 19-22 age brackets, it's interesting to note that I'm sure I wasn't using words characteristic of either in online posts back then (which were only to Usenet anyway) and my current (rather broad) 30-65 age bracket doesn't seem to fit me very well either. Yet I can guess that I do fit in the introverted male corner, minus the Anime and Call of Duty obsessions. Still, guessing's for girls, so since I've been rambling here on this unidirectional social platform for years, time to break out some UNIX one-liners and harvest the hard numbers... Running this command in my phlog directory pops out a 18,769 line file with a count of every word I've ever thrown at you, after only a modest delay even on this 120MHz Pentium 1 PC I'm using: cat *.txt | tr "A-Z ,.;:\"()\`\!?\[\]\\/_\-" "a-z\n" | sort | \ uniq -c | sort -nr > ../../phlog_words.txt The list starts with lots of boring words like all the ones in this sentence. I don't have all the fancy analysis tools to filter them like they did in the study, so I very unscientifically just picked out the more-interesting ones used over 100 times, then manually copied in my less frequently used words which are in the study's word clouds (skipping many, and omitting those I've never used at all). Plus some other interesting ones to compare like good/bad and happy/sad. It's rough, but here's the result (formatted into columns using "pr"): 7499 i 160 idea 107 youtube 14 shit 2692 my 159 modern 107 posts 13 games 1134 i'm 158 server 106 best 13 loving 1126 me 157 great 103 nobody 12 kill 1074 you 155 he 103 documentary 11 taxes 896 i've 154 system 103 build 10 excited 822 their 153 home 102 text 10 fans 690 people 152 data 102 projects 10 hating 623 old 151 page 102 cheap 10 happily 531 gopher 148 thinking 101 worked 9 amazing 500 new 148 online 96 job 8 girlfriend 481 free 145 party 89 country 8 boy 473 internet 145 nice 86 human 7 girls 437 use 144 read 84 hate 7 hacked 471 work 142 government 75 pay 7 super 428 make 140 problem 73 man 6 baby 422 want 138 works 62 love 6 bills 416 think 138 started 59 dream 6 girl 281 need 138 client 53 playing 6 hungry 276 good 138 buy 52 bad 5 birthday 262 world 138 australia 52 tax 5 debt 251 space 137 state 50 pain 5 hated 251 pretty 135 laptop 41 family 5 happier 250 thinker 130 night 43 happy 5 proud 244 web 130 late 38 he's 5 sad 243 software 130 built 33 children 5 wife 243 power 129 war 32 woman 4 dick 242 trying 129 file 31 game 4 loved 239 money 129 content 31 her 4 penis 236 stuff 128 writing 31 she 4 ridiculously 224 his 127 business 28 friends 4 sports 222 working 123 house 28 died 4 sweet 212 your 120 weekend 28 paying 3 daughter 208 computer 119 reading 26 engineering 3 horny 207 running 119 files 25 economy 3 lust 206 life 117 water 24 mother 3 team 194 fact 116 technology 23 tomorrow 3 rent 193 phlog 116 public 22 metal 2 cute 193 keep 114 oil 21 bloody 2 sexy 189 start 113 road 21 father 2 sexually 189 making 113 film 20 sex 2 yay 189 found 113 design 20 shopping 1 360 188 website 113 cost 18 himself 1 bitch 188 doing 112 write 17 fucking 1 boyfriend 187 instead 111 electronics 17 fuck 1 chocolate 181 we 111 building 16 freedom 1 ps3 175 tv 110 photos 16 win 1 she's 174 today 110 past 16 wonderful 1 son 173 car 110 email 15 born 1 sweethearts 173 australia 109 source 15 die 1 sweetheart 173 aussies 109 social 13 president 1 thankful 171 linux 109 phone 14 bullshit 1 wishing 171 finally 108 services 14 cleaning 1 xbox 169 someone 108 makes So yes I indeed fit into the male introvert counts for words like computer and government. Actually I wouldn't use the term introvert to describe myself because I often hear people who in comparison to me are very extroverted describe themselves as introverts, but I guess I'll submit to the terminology of the study. At least it seems my language isn't quite as aggressive as the study seems to paint the average man with all the swearing and fighting talk, though the word 'war' quite a lot. I'm certainly not as lovey-dovey as the women though. Some highlights are that I apparantly 'hate' (84) more than I 'love' (62), but I talk about much more 'good' (276) stuff than 'bad' (52), and more 'happy' (43) than 'sad' (5). I talk much more of 'he' (155) and 'his' (224) than 'she' (31) and 'her' (31 as well). But talk about 'people' (690) in general a lot, and 'you' (1074) and 'your' (212). The 'old' (623) gets a lot of discussion, but the 'new' isn't so far off (500). Finally, for all the time I do spend thinking about 'women' (32) / 'girls' (7), 'loving' (13), 'sex' (20), feelings of 'lust' (3), and being 'horny' (3), I, perhaps mercifully, don't really mention them all that much. The paper talks about how some of the different associations might have misleading implications, and in my case 'party' (145) is, I'm sure, much more associated with my political party reviews posted here than any social gatherings. In the end, t does make me wonder if I should try to be a bit more upbeat in my talk like those women of Facebook. Though in a way I'm glad that I don't fit any group from the study perfectly. - The Free Thinker