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  1. #1
    null Jonny's Avatar
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    Default Tribalism and TypoC

    I've been curious about the relatively recent surge in tribalism since the 2016 election. It is clear to many of us who frequent the politics sub-forum, both as contributors and readers, that here at TypoC we're not immune to this phenomenon. But, unlike our daily interactions in the "real world", here at TypoC we have a wealth of data at our fingertips to shed light on this very issue. By analyzing meta-data on the interactions between forum members, we can better see what lies under the surface.

    So, over the past few days I've been gathering data from the politics sub-forum in a similar(ish) fashion to what was done here: What your posting habits say about you!

    In particular, I've focused on 5 major threads:

    • Trump Administration
    • United States of America - General Thread
    • TRUMP 2016!!!!
    • Europe - general thread
    • 3rd wave feminism


    As of today, I haven't really done much analysis, and I've only gathered very simplistic data like poster names and "likes". However, even this information has been illuminating. Within these threads are just over 16,000 posts by close to 300 members, with a 6,700 likes spread between about 4,500 posts.

    As a simple way to visualize these factions, I decided to extract groups of Likers and Posters. The Likers are those members who liked the most posts within the data set, concentrated between the fewest number of members who posted; for example, if you liked at least 50 different posts, and the members you liked had an average of about 3 likes from you each, you were included in this group. The Posters are those members with the most likes in the data set, concentrated between the fewest number of members who liked them; in other words, if you had at least 30 likes and you received roughly 4 likes from each member who liked you, you were included in this group.

    The reason for including the concentration parameter is to ignore those members who have like 100 likes from 100 different users, since they would likely not represent a "faction" of the forum.

    From this information, I created a matrix for the numbers of likes given by each of the Likers identified above to each of the Posters identified above. I then, very roughly, normalized these numbers to account for the fact that some Likers liked more than others, and some Posters were liked more than others. Below is what came out (after a bit of manual sorting). White colors denote no or very few likes, while green and blue represent increasingly significant concentrations of likes. Squares denoted with an X are for those members who were included in both groups; they're colored blue because I assume (maybe naively, haha) that everyone likes themselves.

    NOTE, IF YOU ARE INCLUDED IN THIS MATRIX I AM IN NO WAY SUGGESTING YOU ARE IN A TRIBE. YOU WERE SIMPLY ONE OF THE MEMBERS IDENTIFIED VIA THE CRITERIA MENTIONED ABOVE. I DIDN'T PICK ANY MEMBER EXPLICITLY.



    Keep in mind that I didn't choose anyone on this list. I set the criteria based on anonymized data, and organized the matrix before knowing who was on it. Then, I converted the anonymous key to member names, and voila! Also, these numbers do not represent the number of likes; they are normalized! So, it isn't the case that Xann liked 0 of my posts; I'm not sure of the exact number but it's at least 1. Rather, based on the average number of likes received and given by everyone in this matrix, I we got a score of 0. Blank squares, however, do denote 0 likes.

    Obviously this analysis is somewhat simplistic; I'll continue to research the best ways to parse and present this information. In addition, I'm curious about analyzing additional data; for example, using a word analyzer to assess the tone/aggression in a post, and flagging users who engage in back-and-forth posting (denoted, for example, by quoting one-another).

    Interesting stuff..

    @Jaguar
    @Magic Poriferan
    @bechimo
    @geedoenfj
    @Floki
    @Totenkindly
    @jcloudz
    @Hard
    @Ivy
    @Lark
    @ChocolateMoose123
    @Poki
    @asynartetic
    @SearchingforPeace
    @SpankyMcFly
    @ZNP-TBA
    @Stephano
    @Xann
    @Tellenbach
    @S16M4
    @DiscoBiscuit
    @YUI
    @Virtual ghost
    @Jonny
    @ceecee
    @Nicodemus

    Likes chickpea, Tellenbach, Kas liked this post

  2. #2
    Senior Member Jaguar's Avatar
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    A small group of people have a large interest in politics. How is that tribalism?
    Likes SearchingforPeace liked this post

  3. #3
    null Jonny's Avatar
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    Quote Originally Posted by Jaguar View Post
    A small group of people have a large interest in politics. How is that tribalism?
    You're right, it isn't necessarily. And, what I'm talking about here might not even meet the formal standard of tribalism, in much the same way getting anxious around a person of color late at night isn't racism. But, it is something. Patterns of behavior can help us know ourselves better; at least I'd like to think so.

    I didn't specifically choose anyone in that matrix, I let the data choose for me. In fact, when I originally came up with the idea and developed the matrix, I had no idea who anyone on that list would be (I'm even on it!).


  4. #4
    Senior Member Jaguar's Avatar
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    Quote Originally Posted by Jonny View Post
    You're right, it isn't necessarily. And, what I'm talking about here might not even meet the formal standard of tribalism, in much the same way getting anxious around a person of color late at night isn't racism. But, it is something. Patterns of behavior can help us know ourselves better; at least I'd like to think so.
    What is your definition of "is"?

  5. #5
    FRACTALICIOUS phobik's Avatar
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    Quote Originally Posted by Jonny View Post
    I've been curious about the relatively recent surge in tribalism since the 2016 election. It is clear to many of us who frequent the politics sub-forum, both as contributors and readers, that here at TypoC we're not immune to this phenomenon. But, unlike our daily interactions in the "real world", here at TypoC we have a wealth of data at our fingertips to shed light on this very issue. By analyzing meta-data on the interactions between forum members, we can better see what lies under the surface.

    So, over the past few days I've been gathering data from the politics sub-forum in a similar(ish) fashion to what was done here: What your posting habits say about you!

    In particular, I've focused on 5 major threads:

    • Trump Administration
    • United States of America - General Thread
    • TRUMP 2016!!!!
    • Europe - general thread
    • 3rd wave feminism


    As of today, I haven't really done much analysis, and I've only gathered very simplistic data like poster names and "likes". However, even this information has been illuminating. Within these threads are just over 16,000 posts by close to 300 members, with a 6,700 likes spread between about 4,500 posts.

    As a simple way to visualize these factions, I decided to extract groups of Likers and Posters. The Likers are those members who liked the most posts within the data set, concentrated between the fewest number of members who posted; for example, if you liked at least 50 different posts, and the members you liked had an average of about 3 likes from you each, you were included in this group. The Posters are those members with the most likes in the data set, concentrated between the fewest number of members who liked them; in other words, if you had at least 30 likes and you received roughly 4 likes from each member who liked you, you were included in this group.

    The reason for including the concentration parameter is to ignore those members who have like 100 likes from 100 different users, since they would likely not represent a "faction" of the forum.

    From this information, I created a matrix for the numbers of likes given by each of the Likers identified above to each of the Posters identified above. I then, very roughly, normalized these numbers to account for the fact that some Likers liked more than others, and some Posters were liked more than others. Below is what came out (after a bit of manual sorting). White colors denote no or very few likes, while green and blue represent increasingly significant concentrations of likes. Squares denoted with an X are for those members who were included in both groups; they're colored blue because I assume (maybe naively, haha) that everyone likes themselves.



    Keep in mind that I didn't choose anyone on this list. I set the criteria based on anonymized data, and organized the matrix before knowing who was on it. Then, I converted the anonymous key to member names, and voila!

    Obviously this analysis is somewhat simplistic; I'll continue to research the best ways to parse and present this information. In addition, I'm curious about analyzing additional data; for example, using a word analyzer to assess the tone/aggression in a post, and flagging users who engage in back-and-forth posting (denoted, for example, by quoting one-another).

    Interesting stuff..

    @Jaguar
    @Magic Poriferan
    @bechimo
    @geedoenfj
    @Floki
    @Totenkindly
    @jcloudz
    @Hard
    @Ivy
    @Lark
    @ChocolateMoose123
    @Poki
    @asynartetic
    @SearchingforPeace
    @SpankyMcFly
    @ZNP-TBA
    @Stephano
    @Xann
    @Tellenbach
    @S16M4
    @DiscoBiscuit
    @YUI
    @Virtual ghost
    @Jonny
    @ceecee
    @Nicodemus
    Jonny, Le Creep strykes hagen.

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    Music provides one of the clearest examples of a much deeper relation between mathematics and human experience.
    Likes Jonny liked this post

  6. #6
    Senior Member Jaguar's Avatar
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    ^ Knew he would show up.

  7. #7
    @.~*virinaĉo*~.@ Totenkindly's Avatar
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    Considering my Likes are pretty low and that I Liked people who I personally dislike if i felt they actually had a good point, i don't think I'd label that "tribalism." But hey, whatever makes you happy.
    "Hey Capa -- We're only stardust." ~ "Sunshine"

    “Pleasure to me is wonder—the unexplored, the unexpected, the thing that is hidden and the changeless thing that lurks behind superficial mutability. To trace the remote in the immediate; the eternal in the ephemeral; the past in the present; the infinite in the finite; these are to me the springs of delight and beauty.” ~ H.P. Lovecraft
    Likes asynartetic liked this post

  8. #8
    ^He pronks, too! Magic Poriferan's Avatar
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    My question is...

    Who the fuck is ChocolateMoose123?
    Go to sleep, iguana.


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    Live and let live will just amount to might makes right
    Likes Jaguar, Jonny, highlander, Ravenetta, Bush and 2 others liked this post

  9. #9
    null Jonny's Avatar
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    Quote Originally Posted by Totenkindly View Post
    Considering my Likes are pretty low and that I Liked people who I personally dislike if i felt they actually had a good point, i don't think I'd label that "tribalism." But hey, whatever makes you happy.
    Yeah, I'm not suggesting anybody on the list is in a tribe or anything. But, the recent surge in tribalism is, rather, what sparked the inquiry in the first place.

    - - - Updated - - -

    Quote Originally Posted by Magic Poriferan View Post
    My question is...

    Who the fuck is ChocolateMoose123?
    Haha, I have no idea. As I said, I didn't pick the people. I let the logic do it...maybe it's someone with very few posts but lots of likes.


  10. #10
    breaking out of my cocoon SearchingforPeace's Avatar
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    Quote Originally Posted by Jonny View Post
    I've been curious about the relatively recent surge in tribalism since the 2016 election. It is clear to many of us who frequent the politics sub-forum, both as contributors and readers, that here at TypoC we're not immune to this phenomenon. But, unlike our daily interactions in the "real world", here at TypoC we have a wealth of data at our fingertips to shed light on this very issue. By analyzing meta-data on the interactions between forum members, we can better see what lies under the surface.

    So, over the past few days I've been gathering data from the politics sub-forum in a similar(ish) fashion to what was done here: What your posting habits say about you!

    In particular, I've focused on 5 major threads:

    • Trump Administration
    • United States of America - General Thread
    • TRUMP 2016!!!!
    • Europe - general thread
    • 3rd wave feminism


    As of today, I haven't really done much analysis, and I've only gathered very simplistic data like poster names and "likes". However, even this information has been illuminating. Within these threads are just over 16,000 posts by close to 300 members, with a 6,700 likes spread between about 4,500 posts.

    As a simple way to visualize these factions, I decided to extract groups of Likers and Posters. The Likers are those members who liked the most posts within the data set, concentrated between the fewest number of members who posted; for example, if you liked at least 50 different posts, and the members you liked had an average of about 3 likes from you each, you were included in this group. The Posters are those members with the most likes in the data set, concentrated between the fewest number of members who liked them; in other words, if you had at least 30 likes and you received roughly 4 likes from each member who liked you, you were included in this group.

    The reason for including the concentration parameter is to ignore those members who have like 100 likes from 100 different users, since they would likely not represent a "faction" of the forum.

    From this information, I created a matrix for the numbers of likes given by each of the Likers identified above to each of the Posters identified above. I then, very roughly, normalized these numbers to account for the fact that some Likers liked more than others, and some Posters were liked more than others. Below is what came out (after a bit of manual sorting). White colors denote no or very few likes, while green and blue represent increasingly significant concentrations of likes. Squares denoted with an X are for those members who were included in both groups; they're colored blue because I assume (maybe naively, haha) that everyone likes themselves.



    Keep in mind that I didn't choose anyone on this list. I set the criteria based on anonymized data, and organized the matrix before knowing who was on it. Then, I converted the anonymous key to member names, and voila!

    Obviously this analysis is somewhat simplistic; I'll continue to research the best ways to parse and present this information. In addition, I'm curious about analyzing additional data; for example, using a word analyzer to assess the tone/aggression in a post, and flagging users who engage in back-and-forth posting (denoted, for example, by quoting one-another).

    Interesting stuff..

    @Jaguar
    @Magic Poriferan
    @bechimo
    @geedoenfj
    @Floki
    @Totenkindly
    @jcloudz
    @Hard
    @Ivy
    @Lark
    @ChocolateMoose123
    @Poki
    @asynartetic
    @SearchingforPeace
    @SpankyMcFly
    @ZNP-TBA
    @Stephano
    @Xann
    @Tellenbach
    @S16M4
    @DiscoBiscuit
    @YUI
    @Virtual ghost
    @Jonny
    @ceecee
    @Nicodemus
    Damn, I actually "liked" one of your posts in these threads you selected, Jonny?!? We must be secret co-conspirators working to disrupt the forum and take over the world!!!!!!!

    I also like reading https://www.theatlantic.com https://www.wsws.org https://www.currentaffairs.org https://www.jacobinmag.com and https://blackagendareport.com daily so they all must be part of a secret conspiracy.

    The data table does look a little like GIGO, TBH. A very few threads. A very few posters. No recognition of the vast amount of interaction off thread between PMs, VMs, reps, and discord/vent. No accounting for changes over time. Etc.

    What I really see are a lot of posters that don't post anymore, even though they are not banned......
    “Orthodoxy means not thinking--not needing to think. Orthodoxy is unconsciousness.”
    ― George Orwell, 1984

    “It is clear that thought is not free if the profession of certain opinions makes it impossible to earn a living. It is clear also that thought is not free if all the arguments on one side of a controversy are perpetually presented as attractively as possible, while the arguments on the other side can only be discovered by diligent search.”

    ― Bertrand Russell, Sceptical Essays
    Likes asynartetic, Falcarius liked this post

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