All language subtitles for 8. Botometer

af Afrikaans
ak Akan
sq Albanian
am Amharic
ar Arabic Download
hy Armenian
az Azerbaijani
eu Basque
be Belarusian
bem Bemba
bn Bengali
bh Bihari
bs Bosnian
br Breton
bg Bulgarian
km Cambodian
ca Catalan
ceb Cebuano
chr Cherokee
ny Chichewa
zh-CN Chinese (Simplified)
zh-TW Chinese (Traditional)
co Corsican
hr Croatian
cs Czech
da Danish
nl Dutch
en English
eo Esperanto
et Estonian
ee Ewe
fo Faroese
tl Filipino
fi Finnish
fr French
fy Frisian
gaa Ga
gl Galician
ka Georgian
de German
el Greek
gn Guarani
gu Gujarati
ht Haitian Creole
ha Hausa
haw Hawaiian
iw Hebrew
hi Hindi
hmn Hmong
hu Hungarian
is Icelandic
ig Igbo
id Indonesian
ia Interlingua
ga Irish
it Italian
ja Japanese
jw Javanese
kn Kannada
kk Kazakh
rw Kinyarwanda
rn Kirundi
kg Kongo
ko Korean
kri Krio (Sierra Leone)
ku Kurdish
ckb Kurdish (Soranî)
ky Kyrgyz
lo Laothian
la Latin
lv Latvian
ln Lingala
lt Lithuanian
loz Lozi
lg Luganda
ach Luo
lb Luxembourgish
mk Macedonian
mg Malagasy
ms Malay
ml Malayalam
mt Maltese
mi Maori
mr Marathi
mfe Mauritian Creole
mo Moldavian
mn Mongolian
my Myanmar (Burmese)
sr-ME Montenegrin
ne Nepali
pcm Nigerian Pidgin
nso Northern Sotho
no Norwegian
nn Norwegian (Nynorsk)
oc Occitan
or Oriya
om Oromo
ps Pashto
fa Persian
pl Polish
pt-BR Portuguese (Brazil)
pt Portuguese (Portugal)
pa Punjabi
qu Quechua
ro Romanian
rm Romansh
nyn Runyakitara
ru Russian
sm Samoan
gd Scots Gaelic
sr Serbian
sh Serbo-Croatian
st Sesotho
tn Setswana
crs Seychellois Creole
sn Shona
sd Sindhi
si Sinhalese
sk Slovak
sl Slovenian
so Somali
es Spanish
es-419 Spanish (Latin American)
su Sundanese
sw Swahili
sv Swedish
tg Tajik
ta Tamil
tt Tatar
te Telugu
th Thai
ti Tigrinya
to Tonga
lua Tshiluba
tum Tumbuka
tr Turkish
tk Turkmen
tw Twi
ug Uighur
uk Ukrainian
ur Urdu
uz Uzbek
vi Vietnamese
cy Welsh
wo Wolof
xh Xhosa
yi Yiddish
yo Yoruba
zu Zulu
Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:00,180 --> 00:00:06,330 Education, you come across someone's Twitter page, sometimes it comes in handy to be able to kind 2 00:00:06,330 --> 00:00:11,610 of figure out if the people that are following him or his friends with are actually on board. 3 00:00:13,110 --> 00:00:19,380 Now the reason behind that is generally, personally, when I'm investigating someone going through 4 00:00:19,380 --> 00:00:25,020 their Twitter page, I like to take a look at who they're following and who their friends are, because 5 00:00:25,530 --> 00:00:29,790 just because they don't post something up doesn't mean that their friends or followers aren't going 6 00:00:29,790 --> 00:00:32,880 to post something out that actually ties information back to them. 7 00:00:33,450 --> 00:00:40,590 So being able to ferret out who is a real person who's a bot comes in really handy, especially if there's 8 00:00:40,590 --> 00:00:44,760 a lot of Twitter followers or a lot of friends with them for that particular target. 9 00:00:46,600 --> 00:00:49,300 Now, one of the programs I like to use is bottom, Peter. 10 00:00:50,290 --> 00:00:52,930 It can be found here at bottom meter dot I. 11 00:00:52,960 --> 00:00:56,710 You and I dot IU dot edu. 12 00:00:57,850 --> 00:01:05,350 Now what -- meter does is or formerly known as Bart or not, Wilczek activity of Twitter account. 13 00:01:05,800 --> 00:01:09,700 And it kind of gives a score to figure out if it's a bot or whether it's a human. 14 00:01:10,570 --> 00:01:13,330 So the higher the score, the more likely they're going to be a bot. 15 00:01:14,470 --> 00:01:19,720 And you could actually click on these little y things here to figure find out more information on that 16 00:01:19,720 --> 00:01:20,230 if you want. 17 00:01:21,040 --> 00:01:24,280 Now, you see, it's pretty easy, so all you need to do is put a screen name in. 18 00:01:24,280 --> 00:01:29,350 So we to do one of mine at Sniper Smurf Dot Sniper Smurf D.H. 19 00:01:29,350 --> 00:01:31,150 So I'm going to check the username, first of all. 20 00:01:33,400 --> 00:01:35,500 And you can see here it comes with the profile. 21 00:01:36,040 --> 00:01:38,860 Nick is a bot score, so 0.7. 22 00:01:39,640 --> 00:01:47,950 Now, clearly, I'm not a bot, so we can check out do check followers, OK, so it's going to go through 23 00:01:47,950 --> 00:01:49,600 all the people that are following me. 24 00:01:52,900 --> 00:01:56,290 And each person is going to be assigned their own score here. 25 00:01:59,290 --> 00:02:02,650 So it looks like a couple of these people are coming up spots. 26 00:02:07,960 --> 00:02:12,700 Campbell, let that run through and real quick, and if we're going to scroll through here, we can 27 00:02:12,700 --> 00:02:20,050 see in the green, so not likely about point five, almost definitely human. 28 00:02:21,400 --> 00:02:27,430 And we have a couple of four point five, four point eight, four point 9s and whatnot. 29 00:02:28,750 --> 00:02:31,390 So let's take one of these real high ones here. 30 00:02:31,870 --> 00:02:35,260 Let's take a look at directivity. 31 00:02:36,980 --> 00:02:44,210 So if we click on any one of these, you could see the content 4.7 sentiment, 4.1 language independent 32 00:02:44,210 --> 00:02:46,640 features and you can to see the score here. 33 00:02:47,120 --> 00:02:48,880 So it gives you a nice little breakdown. 34 00:02:49,140 --> 00:02:53,360 You can do details, you can block a profile on tweets and whatnot. 35 00:02:53,630 --> 00:02:57,770 Now, in order to run this program, you do need to be logged into your Twitter account. 36 00:02:57,770 --> 00:03:06,740 So if you're doing an actual investigation, as always, I recommend using a completely detached profile. 37 00:03:07,400 --> 00:03:10,820 Well, let's say your own open Twitter account. 38 00:03:11,810 --> 00:03:15,710 OK, so I'm going to click on this person here and click profile. 39 00:03:16,010 --> 00:03:19,160 We're going to take a look at what what their Twitter page looks like. 40 00:03:19,850 --> 00:03:22,760 So, yeah, it looks like a lot of random stuff in here. 41 00:03:23,930 --> 00:03:30,610 So doesn't really surprise me that they're coming up as a bot, which they probably are perfectly metric 42 00:03:30,620 --> 00:03:33,170 around the Transbay on this in your garden. 43 00:03:33,170 --> 00:03:37,910 I put panes when your window flower in your mouth, lift me up. 44 00:03:38,630 --> 00:03:39,550 A kiss for love. 45 00:03:39,560 --> 00:03:46,040 Yeah, so probably, probably a but yeah, a lot of random stuff on this Twitter page. 46 00:03:46,730 --> 00:03:55,130 So again, Botto meter really handy for ferreting out real people from bots, not only just checking 47 00:03:55,670 --> 00:03:58,820 Twitter accounts of your target, but also friends and followers. 48 00:04:00,320 --> 00:04:06,590 And again, to use it really easy at and whatever the username they click on, check user check followers, 49 00:04:06,590 --> 00:04:11,210 check friends and they can be found at bottom feeders that are you? 50 00:04:11,210 --> 00:04:14,270 And I talked IU Dot Edu. 51 00:04:14,720 --> 00:04:15,530 Thank you for watching. 5420

Can't find what you're looking for?
Get subtitles in any language from opensubtitles.com, and translate them here.