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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

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