Collective Intelligence on YouTube

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    • 00:00

      [SAGE video case studies][Collective Intelligence on YouTube]

    • 00:09

      SIMON LINDGREN: Hi.I'm Simon Lindgren.I'm a professor of sociology at Umea University in Sweden.I'm an internet researcher.I look at social media and how people use social mediaas tools for achieving various goals,organizing, mobilizing in both political and culturalcontexts.In this case study, we'll look at howthe theories of collective intelligence and participatory

    • 00:30

      SIMON LINDGREN [continued]: culture relate to the real world.We look at YouTube, and we will lookat user reactions to different video genresand how these reactions might relateto various forms of learning.[YouTube and Learning]When we're talking about YouTube and collective intelligence,we need to start with YouTube itself.

    • 00:51

      SIMON LINDGREN [continued]: This site is definitely at the centerof what's been called the social media revolution.YouTube might be the most successful siteon the internet.It has 50,000 videos viewed per second, 700 tweets per minutelinked to YouTube, and only through Facebook 500years of video are watched on YouTube every day.

    • 01:12

      SIMON LINDGREN [continued]: But can YouTube be a place for learning?At least it's a place of social activity,because millions of people are active there every day,liking videos, sharing videos, commenting and respondingto them in various ways.Also, people are uploading videos, being creative.So it's not only an archive.It's sort of a community.Theorist James Paul Gee has written about something

    • 01:34

      SIMON LINDGREN [continued]: he calls "affinity spaces," whichare places that might emerge online,where people come together because of common interests.They go to these places to be creativeand to exchange knowledge and skills.But in contrast to perspectives like that,we also know that the internet isfull of bad things-- online hate, cyberbullying,the use of harsh language, so-called trolls.

    • 01:56

      SIMON LINDGREN [continued]: People feel the distance and indifference in relationto each other.So in this case study, we'll lookat if learning works on a social platform like YouTubeand, if so, how it works.[Measuring Affinity]To analyze these things closer, Imade a study of 24,000 comments to YouTube clips.

    • 02:18

      SIMON LINDGREN [continued]: So I selected six popular clips thatwere representing six different categories of videoson YouTube-- one from the news category;one from the gaming category; an entertainment clip,which was a music video; a video blog; a tutorial video;and a travel video.And what I wanted to look at was the climatein the comment threads.

    • 02:39

      SIMON LINDGREN [continued]: Were there are any differences in the discussions?And I was specifically interested in the feelingsexpressed in these discussions.So I used a method called sentiment analysis, whichcan measure positive and negative emotions in text.So I used to particular tool-- this one's calledSentiStrength-- to process all of these 24,000 comments.And the tool calculates two scores for each comment-- one

    • 03:02

      SIMON LINDGREN [continued]: positive score between plus 1 and plus 5,and one negative score between minus 1 and minus 5.So a very positive expression would be plus 5 and minus 1,and a highly negative would be plus 1 and minus 5.So a balanced comment would be plus 2 and minus 2,for example.And when I looked at these 24,000 comments,

    • 03:23

      SIMON LINDGREN [continued]: I found it most of them, 85%, were quite neutral.But the interesting thing was that the tutorial video, whichwas a young girl putting on goth makeup,got the most positive response.And the gaming video and the video bloggot similar patterns.But the other three-- the music video,the news, and the travel clips-- got more neutral or negative

    • 03:43

      SIMON LINDGREN [continued]: responses.So one conclusion might be that, for user generated content,there are more positive responses.While for traditionally produced content,there are more neutral or negative responses.So it might seem then as if videosthat are produced by users themselveshave a higher degree of affinity around them, whichmeans that there's a tighter knit community around them

    • 04:05

      SIMON LINDGREN [continued]: that might promote learning.So looking even closer at this, Idecided to compare two of these categoriess--the how-to videos and the news videos.So then I chose the 10 most commented clipsper category and the 1,000 most recent comments to all of them.So then I had a data set of 20,000 comments.

    • 04:26

      SIMON LINDGREN [continued]: And I made a similar sentiment analysis for these.And it was the same pattern, actually.Then news videos got more neutral or negative responses,and the how-to videos got more positive responses.[Content analysis of comments]To get to know even more about this,

    • 04:47

      SIMON LINDGREN [continued]: I made a network analysis of words and conceptsthat were occurring in these discussions.And I found then four themes.First, one theme revolving around the word"like" and positive netspeak abbreviations like LOL.People discussing finding things,knowing things, posting questions, and so on.The second theme was about doing things-- doing things yourself,

    • 05:09

      SIMON LINDGREN [continued]: making things work, and so on.Finally, I found two larger themesthat seemed to be interconnected with key concepts like videosand thanks.So we found then a number of positive exclamations-- peoplesaying that stuff was cool, it was nice, they loved it,it was perfect, and so on.Also, people were exchanging knowledge

    • 05:31

      SIMON LINDGREN [continued]: with discourse-like pleas, need, want, using the word "help,"and so on.People were also mentioning thingslike method, show, instructions, tutorial, teach, and so on.And finally, people were saying that things were solved,that they understood things, and they were expressingtheir thanks, and so on.So in some, there was discourse that could be identified,

    • 05:54

      SIMON LINDGREN [continued]: which was revolving around helpfulness,around positive encouragement, and around Knowledge Exchange.So we saw examples then of peopleexpressing gratefulness and encouragement,saying that this video was good, that they wanted morefrom this video producer.Also, we saw examples of people posting,saying that, well, this was a good tutorial.Now I'm going off to try this myself.

    • 06:15

      SIMON LINDGREN [continued]: Furthermore, we saw examples of people getting backto the discussion thread, reporting results of tryingthe tutorial instructions out.We also saw some more examples that,even though there's no long-term commitment to these threads,maybe there are some suggestions that people actuallytake the time to provide constructive criticismand to suggest alterations to the videos.

    • 06:36

      SIMON LINDGREN [continued]: Finally, we saw examples of these videos generatingfurther dialogues, new group discussions on new topics thatwere arising.So there were traces that the interaction actuallycontinued beyond the scope of these particular videos.[Conclusions]In conclusion then, there are indeed affinity spaces

    • 06:57

      SIMON LINDGREN [continued]: around these videos.There are some sort of interactive sites around them,where people can come together with common goalsand common interests or activities.So it's not people's identities or the factthat the group must be homogeneousthat's at the center.The videos established spaces where beginners and expertsmight meet.And even though the tutorials might be about very

    • 07:18

      SIMON LINDGREN [continued]: everyday things, these processes illustrate that people todayare increasingly taking part in knowledge cultures thatare quite removed from formal settings.And even though this is not new as such,with social media and the internet,the reach, intensity, the volume,and the speed of these processes increase.

Collective Intelligence on YouTube

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Abstract

Prof. Simon Lindgren analyzes You Tube user comments to identify if You Tube is a viable forum for exchanging knowledge and if such exchanges are positive experiences.

SAGE Video Cases
Collective Intelligence on YouTube

Prof. Simon Lindgren analyzes You Tube user comments to identify if You Tube is a viable forum for exchanging knowledge and if such exchanges are positive experiences.

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