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Isis Meme: Oh shit! #isis #meme #memes #dankmeme #cringe #cringeworthy ...
Isis Meme: Oh shit! #isis #meme #memes #dankmeme #cringe #cringeworthy ...

Oh shit! #isis #meme #memes #dankmeme #cringe #cringeworthy ...

Isis Meme: Oh shit! #isis #meme #memes #dankmeme #cringe #cringeworthy ...
Isis Meme: Oh shit! #isis #meme #memes #dankmeme #cringe #cringeworthy ...

Oh shit! #isis #meme #memes #dankmeme #cringe #cringeworthy ...

Isis Meme: Oh shit! #isis #meme #memes #dankmeme #cringe #cringeworthy ...
Isis Meme: Oh shit! #isis #meme #memes #dankmeme #cringe #cringeworthy ...

Oh shit! #isis #meme #memes #dankmeme #cringe #cringeworthy ...

Isis Meme: Oh shit! #isis #meme #memes #dankmeme #cringe #cringeworthy ...
Isis Meme: Oh shit! #isis #meme #memes #dankmeme #cringe #cringeworthy ...

Oh shit! #isis #meme #memes #dankmeme #cringe #cringeworthy ...

Isis Meme: pepe sad-frog savepepe smug-frog-b anti-meme smug-frog-a apustaja 0.6 0.4: 02- Figure 6: Inter-cluster distance between allelusters with frog memes. Clusters are labeled with the origin (4 for 4chan, D for The Donald, and G for Gab) and the meme name. To ease re adabi lity, we do not display all labels, abbreviate meme names, and only show an excerpt of all relationships in /pol, we find the #TrumpAnime controversy event [55] Although, due o space constraints, this analysis is limited where a political individual (Rick Wilson) offended the alt right community, Donald Trump supporters, and anime fans (an oddly intersecting set of interests of /pol/ users). Simi larly, on The Donald and Gab, we find the #Cnnblack mail [31] event, refering to the (alleged) blackmail of the Reddit user that created the infamous video of Donald Tnump wresding the CNN to a single "family" of memes, our distance metric can actu ally provide useful insights regarding the phylogenetic rela tionships of any clusters. In fact, more extensive an alysis of these relationships (through our pipeline) can facilitate the un derstanding of the diffusion of ideas and infomation across the Web, and provide a rigorous technique for large-scale analysis of Intemet culture. 4.1.2 Memes' Branching Nature 4.1.3 Meme Visualization We also use the custom distance metric (see Equation 1) to visualize the clusters with annotations. We build a graph G =(V.E), where V are the medoids of annotated clus- Next, we study how memes evolve by looking at variants across different clus ers. Intuitively, clusters that look alike and/or are part of the same meme are grouped together under the same branch of an evolutionary tree. We use the custom distance metric introduced in Section 2.3, aiming to infer the phylogenetic relationship between variants of memes. Since there are 12.6K annotated clusters, we only report on a subset ters and E the connections between medoids with distance un- der a threshold K. Figure 7 shows a snapshot of the graph for K0.45, chosen based on the frogs analysis dis cussed above. In particular, we select this thresho kd as the majority of the clusters from the same meme (note coloration in Figure 6) are hierarchically connected with a hig her-level cluster at a dis tance close to 045. of variants. In particular, we focus on "frog" memes (c.g., Pepe the Frog [45]): as discussed later in Section 4.2, this is one of the most popular memes in our datasets To case readability, we filter out nodes and edges that have a sum of in- and out-degree less than 10, which leaves 40 % of the nodes and 92% of the edges. Nodes are colored according to their KYM annotation. NB: the graph is laid out using the OpenOrd algorithm [61] and the distance between the compo- nents in it does not exactdly match the actual distance metric. The dendrogram in Figure 6 shows the hierarchical rela tonship between groups of clusters of memes related to frogs. Overall, there are 525 clusters of frogs, belonging to 23 differ ent memes. The se clusters can be grouped into four large cat egories, dominated by Apu Apustaja [27], Feels Bad Man/Sad Frog [35]. Pepe the Frog [45], and Smug Frog [52]. The dif ferent memes express different ideas or messages: e.g., Apu Apustaja depicts a simple-minded non-native speaker using broken English, while the Feels Bad ManSad Frog (ironically) expresses dismay at a given situation, often accompanied with We observe a large set of disconnected components, with each component containing nodes of primarily one color. This indi cates that our distance metric is indeed capturing the peculiar ities of different memes. Finally, note that an interactive version of the full graph is publicly availabk from [ ave X" The dendrogram "You will never do/be text shows a variant of Smug Frog (smueg-frog-b) related to a vari ant of the Russ ian Anti Meme Law [51] (anti-meme) as well as relationships between clusters from Pepe the Frog and Isis meme [38], and between Smug Frog and Brexit-related clus- ters [56], as shown in Appendix C The distance metric quantifies the similarity of any two vari 4.2 Web Community-based Analysis We now present a macro-perspective analysis of the Web communities through the lens of memes. We assess the pres- ence of different memes in each community, how popular they are, and how they evolve. To this end, we examine the posts from all four communities (Twitter, Reddit, /pol/, and Gab) that contain images matching memes from fringe Web communities /pol, The Donald, and Gab) ants of different memes; however, recall that two clusters can be close to each other even when the medoids are perceptually different (see Section 2.3), as in the case of Smug Frog variants in the smug-frog-a and smug-frog-b clusters (top of Figure 6) 8 aouesa On the Origins of Memes by Means of Fringe Web Communities
Isis Meme: pepe
 sad-frog
 savepepe
 smug-frog-b anti-meme
 smug-frog-a
 apustaja
 0.6
 0.4:
 02-
 Figure 6: Inter-cluster distance between allelusters with frog memes. Clusters are labeled with the origin (4 for 4chan, D for The Donald, and
 G for Gab) and the meme name. To ease re adabi lity, we do not display all labels, abbreviate meme names, and only show an excerpt of all
 relationships
 in /pol, we find the #TrumpAnime controversy event [55]
 Although, due o space constraints, this analysis is limited
 where a political individual (Rick Wilson) offended the alt
 right community, Donald Trump supporters, and anime fans
 (an oddly intersecting set of interests of /pol/ users). Simi
 larly, on The Donald and Gab, we find the #Cnnblack mail [31]
 event, refering to the (alleged) blackmail of the Reddit user
 that created the infamous video of Donald Tnump wresding
 the CNN
 to a single "family" of memes, our distance metric can actu
 ally provide useful insights regarding the phylogenetic rela
 tionships of any clusters. In fact, more extensive an alysis of
 these relationships (through our pipeline) can facilitate the un
 derstanding of the diffusion of ideas and infomation across the
 Web, and provide a rigorous technique for large-scale analysis
 of Intemet culture.
 4.1.2 Memes' Branching Nature
 4.1.3 Meme Visualization
 We also use the custom distance metric (see Equation 1)
 to visualize the clusters with annotations. We build a graph
 G =(V.E), where V are the medoids of annotated clus-
 Next, we study how memes evolve by looking at variants
 across different clus ers. Intuitively, clusters that look alike
 and/or are part of the same meme are grouped together under
 the same branch of an evolutionary tree. We use the custom
 distance metric introduced in Section 2.3, aiming to infer the
 phylogenetic relationship between variants of memes. Since
 there are 12.6K annotated clusters, we only report on a subset
 ters and E the connections between medoids with distance un-
 der a threshold K. Figure 7 shows a snapshot of the graph for
 K0.45, chosen based on the frogs analysis dis cussed above.
 In particular, we select this thresho kd as the majority of the
 clusters from the same meme (note coloration in Figure 6) are
 hierarchically connected with a hig her-level cluster at a dis
 tance close to 045.
 of variants. In particular, we focus on "frog" memes (c.g., Pepe
 the Frog [45]): as discussed later in Section 4.2, this is one of
 the most popular memes in our datasets
 To case readability, we filter out nodes and edges that have
 a sum of in- and out-degree less than 10, which leaves 40 % of
 the nodes and 92% of the edges. Nodes are colored according
 to their KYM annotation. NB: the graph is laid out using the
 OpenOrd algorithm [61] and the distance between the compo-
 nents in it does not exactdly match the actual distance metric.
 The dendrogram in Figure 6 shows the hierarchical rela
 tonship between groups of clusters of memes related to frogs.
 Overall, there are 525 clusters of frogs, belonging to 23 differ
 ent memes. The se clusters can be grouped into four large cat
 egories, dominated by Apu Apustaja [27], Feels Bad Man/Sad
 Frog [35]. Pepe the Frog [45], and Smug Frog [52]. The dif
 ferent memes express different ideas or messages: e.g., Apu
 Apustaja depicts a simple-minded non-native speaker using
 broken English, while the Feels Bad ManSad Frog (ironically)
 expresses dismay at a given situation, often accompanied with
 We observe a large set of disconnected components, with each
 component containing nodes of primarily one color. This indi
 cates that our distance metric is indeed capturing the peculiar
 ities of different memes.
 Finally, note that an interactive version of the full graph is
 publicly availabk from [
 ave X" The dendrogram
 "You will never do/be
 text
 shows a variant of Smug Frog (smueg-frog-b) related to a vari
 ant of the Russ ian Anti Meme Law [51] (anti-meme) as well
 as relationships between clusters from Pepe the Frog and Isis
 meme [38], and between Smug Frog and Brexit-related clus-
 ters [56], as shown in Appendix C
 The distance metric quantifies the similarity of any two vari
 4.2 Web Community-based Analysis
 We now present a macro-perspective analysis of the Web
 communities through the lens of memes. We assess the pres-
 ence of different memes in each community, how popular they
 are, and how they evolve. To this end, we examine the posts
 from all four communities (Twitter, Reddit, /pol/, and Gab) that
 contain images matching memes from fringe Web communities
 /pol, The Donald, and Gab)
 ants of different memes; however, recall that two clusters can
 be close to each other even when the medoids are perceptually
 different (see Section 2.3), as in the case of Smug Frog variants
 in the smug-frog-a and smug-frog-b clusters (top of Figure 6)
 8
 aouesa
On the Origins of Memes by Means of Fringe Web Communities

On the Origins of Memes by Means of Fringe Web Communities