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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Triangles to Capture Social Cohesion · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1107.3231/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1107.3231/feed.xml" rel="self" type="application/rss+xml" /><item><title>Triangles to Capture Social Cohesion — mentioned by friggeri</title><link>https://news.ycombinator.com/item?id=3901346</link><guid isPermaLink="false">urn:hackerpapers:mention:1107.3231:3901346</guid><pubDate>Fri, 27 Apr 2012 22:40:21 GMT</pubDate><description>&lt;p&gt;Thanks, the algorithm is a heuristic which optimize a quantity I&amp;#x27;ve called social cohesion (http://arxiv.org/pdf/1107.3231.pdf), the article presenting the algorithm itself is currently under review, but basically: first it computes the best possible group for selected edges in the graph, then it merge groups which overlap too much. The whole difficulty is to identify how to select those edges, how to expand around them and then what does &amp;quot;too much overlap&amp;quot; means. I&amp;#x27;ll link to the preprint as soon as I upload it to arxiv. What do you mean exactly by &amp;quot;detect&amp;quot; issues? C^3 should work if there…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1107.3231/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.SI</category></item><item><title>Triangles to Capture Social Cohesion — mentioned by friggeri</title><link>https://news.ycombinator.com/item?id=3901330</link><guid isPermaLink="false">urn:hackerpapers:mention:1107.3231:3901330</guid><pubDate>Fri, 27 Apr 2012 22:35:38 GMT</pubDate><description>&lt;p&gt;I was not aware of this xkcd comic, funny how things seem to pop out. My inspiration was more in the line of Sankey diagrams. Among others, the famous map of Napoleon&amp;#x27;s invasion of Russia by Minard (http://en.wikipedia.org/wiki/File:Minard.png). I&amp;#x27;ve called this representation a &amp;quot;groupflow&amp;quot; but any name would do. The notion of agreement departs a little bit from the classical fraction of common votes/total votes and instead is based on a vector model of votes, using cosine similarity as a value of agreement. The agreement groups are computed by heuristically optimizing a quantity called the…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1107.3231/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.SI</category></item><item><title>Triangles to Capture Social Cohesion — mentioned by friggeri</title><link>https://news.ycombinator.com/item?id=3238523</link><guid isPermaLink="false">urn:hackerpapers:mention:1107.3231:3238523</guid><pubDate>Tue, 15 Nov 2011 15:33:26 GMT</pubDate><description>&lt;p&gt;Related to this, I&amp;#x27;m a PhD student from INRIA[1] and as part of my research on social communities I launched at the beginning of the year an experiment called Fellows[2] on Facebook doing more or less the same thing as Katango. Except that Fellows was not an iphone app but a web experiment which aim was validate a new quantification of social cohesion I have introduced (the results were presented in a peer reviewed conference, the final manuscript is on arxiv [3]). I have been wondering about the difference of media treatment Katango and Fellows received. I tried everything imaginable at the…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1107.3231/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.SI</category></item></channel></rss>
