 And next we have Gilad Lothan who Ethan has already pointed out is a master coder, but he's also multi-talented So he works at social flow Additionally, he is also one of fairly few people who do something like that who also publishes academic articles and Also blogs at global voices and I could go on and on but in the interest of time I'll let him take it. It's really great to be here I'm gonna go over a bunch of data points, which I think are interesting and might help us Take this conversation forward. So I'm Gilad. I'm Chief scientist at a startup called social flow in New York City And I look at a lot of data In my in my daily routine, so we mined the full Twitter fire hose the full bitly fire hose We build that into a product But a lot of what I do is try to find out interesting things that we see in the data and tell stories from it So lo and behold humanity is fairly consistent. We talk about we would mention mornings in the mornings We get tired sort of towards the evenings Talk about coffee more frequently in the morning. These are the sort of normal diurnal patterns that we see on Twitter, right? as expected but it's actually When when interesting events happen and events that are out of the ordinary that happen It's very clear that they happen. So these are two very different trends on Twitter, right? One is your typical Hashtag that goes viral. So in this case, it's hash blame the Muslims starts Very locally in London. It started right after the events in Norway, right? So instantly sort of different Muslim organizations were blamed for what happened in Norway actually a Muslim Twitter user in around London Started this hashtag and was saying, oh, you know, your your clock is broken. Why don't you blame the Muslims? Oh, yeah, your car is not working Just blame the Muslims and she and her friends. I don't know what's happening here. She and her friends were We're sort of using the hashtag for snark It sort of spread locally within their community but died down at night in the morning total loss of context spreads Thoroughly on Twitter Becomes globally trending and then sort of dies down. Alright, so we see an organic trend. We see it grow We see loss of context. So that's interesting. Is that misinformation? It's people who saw this hashtag in our in our thinking. It's something very different, right? There are people who got really angry and said how dare Twitter have this is trending like this is not okay But it started as a joke a local joke spread and then dies down. That's totally organic We see this all the time what we see in green is how a spam bot network looks like, right? So you you see these steps happen, right? It's as if someone's turning on turning a crank like okay add more tweets Okay, 50,000 more tweets more tweets that it then like take them down and what happens here We suspect it's sort of it somehow reached some organic growth. So it sort of started somehow growing in organic Traffic Twitter caught it shut it down and then it died, right? So this stuff we could see we could clearly see this kind of stuff happening on Twitter just by looking at at the Dynamics of like the levels of data It's so easy to tell another thing that that we could tell is is throughout all these social signals So we all know Justin Bieber and a screaming fans on Twitter This is sort of this is how much traffic he garners how many retweets he gets in comparison to Pavel Globa Who's probably the most retweeted person on Twitter? Thousands and thousands and thousands of retweets, but we didn't we never get to see him because his content Looks looks something like this, right? You see lots of eggs. We see sort of I mean he writes in Russian He gets a ton of retweets by the way, he predicted that The Mayans were not right so 2012 were safe. The world is not ending. He's getting a ton of retweets for that But but obviously the social structure of the network is not and the way we sort of build our networks in these spaces Mean that we like we don't get to see a lot of this content because we wouldn't subscribe subscribe to it This is another thing that we can get from looking at data There's an analysis that we ran on Trending topics on Twitter few Google Occupy Wall Street trending topics you'll you'll see a Sort of better explanation for what this means, but in effect when you actually look at the data and you see what What topics are competing with so levels of attention that Occupy Wall Street in blue is competing with like Kim Kardashian's wedding, right? Steve Jobs death you'll see that The way we built these algorithms right the way these algorithms promote certain trends to trending topics means we will never see anything That's so sort of slowly slowly growth Um This is an interesting example of context setting right another information flow. This is how the news about Osama bin Laden broke So Keith Urban who used to be chief of staff of Donald Rumsfeld wrote he got off the phone He's like so I'm told by a reputable person. They've killed Osama bin Laden, right? He didn't have a huge following He didn't have a huge network But he had people who sort of set his post in context who said you know Jake Sherman for Politico Rumsfeld chief Says this Brian Stelter of the New York time also pointed to the fact that he used to be Rumsfeld's chief All right, so with without that context setting we suspect the the the information wouldn't have spread as far Right, that was a case of truthful information that spread a rumor that spread really far This is a case of supposedly false information that spread quite far So we at the height of Occupy Wall Street Chopper Chopper was told by supposedly told by New York PD to move that they're closing the airspace So NBC post posted this sort of it garnered a lot of responses And they had to retract it because New York sort of it's still unclear what exactly happened But supposedly New York PD New York police department Said that there was a pilot misunderstood what they were asking him etc So what we see with when we actually look at the traffic the green is the misinformation So there's substantially more responses to the actual misinformation then then the retraction of it, right? But this is not This this is not always the case. It's just the case for this specific Event and they're actually all these issues with these events But the the the more interesting question that we should be asking is First of all what other what other posts about the misinformation went out, right? Not the formal ones from NBC also who who participated in in the misinformation versus the information and a lot of that We can get from the data so I I Think I'm gonna stop here because we're running out of time And we'll continue the the actual panel Yeah, thank you. Thank you so much