Comments for Gilad Lotan http://giladlotan.com/blog musings on big data, visualization and politics Wed, 08 May 2013 02:19:50 +0000 hourly 1 http://wordpress.org/?v=3.4.2 Comment on Mapping Twitter’s Python and Data Science Communities by keyError in python when using networkx pakcage to visualize data - How-To Video http://giladlotan.com/blog/mapping-twitters-python-data-science-communities/comment-page-1/#comment-60419 keyError in python when using networkx pakcage to visualize data - How-To Video Wed, 08 May 2013 02:19:50 +0000 http://giladlotan.com/blog/?p=953#comment-60419 [...] Anyone knows how to fix it? I’m really a newbie to python and Gephi. I blog I referred when creating my code is giladlotan.com/blog/mapping-tw… [...] [...] Anyone knows how to fix it? I’m really a newbie to python and Gephi. I blog I referred when creating my code is giladlotan.com/blog/mapping-tw… [...]

]]> Comment on Back to Beta by Greg Battle http://giladlotan.com/blog/back-to-beta/comment-page-1/#comment-60291 Greg Battle Fri, 29 Mar 2013 18:16:25 +0000 http://giladlotan.com/blog/?p=1050#comment-60291 Good luck Gilad! I look forward to marveling at your next creations. GB Good luck Gilad!

I look forward to marveling at your next creations.

GB

]]> Comment on Back to Beta by Devin Gaffney http://giladlotan.com/blog/back-to-beta/comment-page-1/#comment-60290 Devin Gaffney Fri, 29 Mar 2013 17:10:12 +0000 http://giladlotan.com/blog/?p=1050#comment-60290 Woo! Congrats Gilad! Woo! Congrats Gilad!

]]> Comment on Did Pew just Prove that Crimson Hexagon’s Twitter Sentiment Analysis Technology is Meaningless? by Alex http://giladlotan.com/blog/did-pew-just-prove-that-crimson-hexagons-twitter-sentiment-analysis-technology-is-meaningless/comment-page-1/#comment-60247 Alex Mon, 18 Mar 2013 18:11:06 +0000 http://giladlotan.com/blog/?p=1025#comment-60247 It's my understanding that Crimson Hexagon is based off of Gary King's ReadMe package (http://gking.harvard.edu/readme), which is an implementation of his non-parametric machine learning method of classification (http://gking.harvard.edu/files/gking/files/words.pdf). It’s my understanding that Crimson Hexagon is based off of Gary King’s ReadMe package (http://gking.harvard.edu/readme), which is an implementation of his non-parametric machine learning method of classification (http://gking.harvard.edu/files/gking/files/words.pdf).

]]> Comment on Did Pew just Prove that Crimson Hexagon’s Twitter Sentiment Analysis Technology is Meaningless? by Nate Angell http://giladlotan.com/blog/did-pew-just-prove-that-crimson-hexagons-twitter-sentiment-analysis-technology-is-meaningless/comment-page-1/#comment-60246 Nate Angell Mon, 18 Mar 2013 18:09:06 +0000 http://giladlotan.com/blog/?p=1025#comment-60246 Thanks for the shoutout for <a href="http://getlittlebird.com" rel="nofollow">Little Bird</a> (where I work with @marshallK)...we agree you are on to something with valuing a contextual, network-based analysis over content analysis. Attending a recent talk on #bigdata by @Viktor_MS and @kncukier, I was struck by their pointing out how essentially having ALL the data from a source rather than just samples enables/forces us to continually reinvent/refashion our interpretive lenses. Maybe that refashioning is what you're onto here. = Nate Angell, Doorman Little Bird http://xolotl.org @xolotl Thanks for the shoutout for Little Bird (where I work with @marshallK)…we agree you are on to something with valuing a contextual, network-based analysis over content analysis.

Attending a recent talk on #bigdata by @Viktor_MS and @kncukier, I was struck by their pointing out how essentially having ALL the data from a source rather than just samples enables/forces us to continually reinvent/refashion our interpretive lenses. Maybe that refashioning is what you’re onto here.

= Nate Angell, Doorman
Little Bird
http://xolotl.org
@xolotl

]]> Comment on Mapping Twitter’s Python and Data Science Communities by Data Nerd http://giladlotan.com/blog/mapping-twitters-python-data-science-communities/comment-page-1/#comment-60054 Data Nerd Thu, 27 Dec 2012 17:57:29 +0000 http://giladlotan.com/blog/?p=953#comment-60054 My name [data_nerd] "was" mentioned, not for my 15 years with data analysis, my skills in programming and data cleansing, the fact that I have worked with data from Fortune 100 companies nor my 2 years talking about Data Science and Analytics on Twitter to educate anyone that is interested but for being NOISY :o) Nice analysis! My name [data_nerd] “was” mentioned, not for my 15 years with data analysis, my skills in programming and data cleansing, the fact that I have worked with data from Fortune 100 companies nor my 2 years talking about Data Science and Analytics on Twitter to educate anyone that is interested but for being NOISY :o ) Nice analysis!

]]> Comment on Mapping Twitter’s Python and Data Science Communities by Big Data News Roundup: The Where, Who, and Why of Data Scientists - About-Dogs.co http://giladlotan.com/blog/mapping-twitters-python-data-science-communities/comment-page-1/#comment-60047 Big Data News Roundup: The Where, Who, and Why of Data Scientists - About-Dogs.co Tue, 25 Dec 2012 00:57:02 +0000 http://giladlotan.com/blog/?p=953#comment-60047 [...] work still matters in the virtual world that was supposed to kill geography, was also endorsed by Gilad Lotan’s mapping of interactions among data scientists on Twitter, finding distinct East Coast and West Coast [...] [...] work still matters in the virtual world that was supposed to kill geography, was also endorsed by Gilad Lotan’s mapping of interactions among data scientists on Twitter, finding distinct East Coast and West Coast [...]

]]> Comment on Mapping Twitter’s Python and Data Science Communities by Sunday data/statistics link roundup 12/23/12 | Simply Statistics http://giladlotan.com/blog/mapping-twitters-python-data-science-communities/comment-page-1/#comment-60043 Sunday data/statistics link roundup 12/23/12 | Simply Statistics Sun, 23 Dec 2012 14:44:55 +0000 http://giladlotan.com/blog/?p=953#comment-60043 [...] A map of data scientists on Twitter.  Unfortunately, since we don’t have “data scientist” in our Twitter description, Simply Statistics does not appear. I’m sure we would have been central…. [...] [...] A map of data scientists on Twitter.  Unfortunately, since we don’t have “data scientist” in our Twitter description, Simply Statistics does not appear. I’m sure we would have been central…. [...]

]]> Comment on Mapping Twitter’s Python and Data Science Communities by Pick of the week links for programmers « Cogitas Blog http://giladlotan.com/blog/mapping-twitters-python-data-science-communities/comment-page-1/#comment-60042 Pick of the week links for programmers « Cogitas Blog Sat, 22 Dec 2012 11:14:44 +0000 http://giladlotan.com/blog/?p=953#comment-60042 [...] Mapping Twitter’s Python and Data Science Communities – a self referential demonstration of Python’s Networkx library and the open source graphing tool, Gephi, by mapping Twitter users who refer to Python in their bio. Neat. [...] [...] Mapping Twitter’s Python and Data Science Communities – a self referential demonstration of Python’s Networkx library and the open source graphing tool, Gephi, by mapping Twitter users who refer to Python in their bio. Neat. [...]

]]> Comment on Mapping Twitter’s Python and Data Science Communities by giladlotan http://giladlotan.com/blog/mapping-twitters-python-data-science-communities/comment-page-1/#comment-60041 giladlotan Fri, 21 Dec 2012 18:53:58 +0000 http://giladlotan.com/blog/?p=953#comment-60041 Martin - totally. This was done as a fun experiment for a python tutorial. The next step would be to used these terms as "seeds" to identify part of the community. Then use the network signals to identify others who are core to the community, but do ont have those words in their bios (think highly interconnected nodes who are outside of the existing set of nodes). I wanted to add that as a next step but just didn't have the time... Perhaps over the next week when there's a bit more time. Martin – totally.
This was done as a fun experiment for a python tutorial.
The next step would be to used these terms as “seeds” to identify part of the community. Then use the network signals to identify others who are core to the community, but do ont have those words in their bios (think highly interconnected nodes who are outside of the existing set of nodes). I wanted to add that as a next step but just didn’t have the time… Perhaps over the next week when there’s a bit more time.

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