Posted by on Jul 31, 2015 in Uncategorized | 0 comments

A new website for the SoMe Lab @ UW is being developed and should be available before the end of September.  We’ll keep this site, even though we have not kept it up-to-date.  When the newer site is published, we will link to this original site for those interested in the historical record.  The older posts and links to articles will remain for the foreseeable future.


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Ephemerality and decay and erosion. Oh my!

Posted by on Feb 21, 2014 in Methods | 0 comments

cross stitched 404 Not Found ImageOne of the oft-discussed challenges of working with social media data, especially Twitter, is the ephemeral nature of the data.  If we do not collect the data in real-time, it disappears.  While it is possible could purchase historical data from GNIP or DataSift; the cost is out of reach of most researchers. It’s easy to think that we’ve dodged that bullet of ephemerality once we’ve built an archive of tweets and other social media data about a specific event or topic.  But have we? 

What about the URLs in these tweets?

Twitter is a microblogging service in which the text of each message or tweet is up to 140 characters long.  The tweet text can contain various elements including mentions of other users, hashtags, emoji, and URLs.  What happens when a URL is included in the text of the tweet? Do the contents of the URL become part of the tweet?  Can you understand the content and context of the tweet if you only read the text alone?  Does the URL, in a way, extend the text of the tweet beyond 140 characters?  

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The Magic of Metaphors

Posted by on Feb 20, 2014 in Ethics, Methods, Modeling, Research | 0 comments

curious rabbit

Metaphors are magical.  Unlike similes or analogs, which express a one-to-one mapping of concepts, metaphors are equivocal; they imply and suggest qualities that are not immediately apparent.  Presented with a simile, we can accept or reject it.  Offered a metaphor, we’re likely to respond with a “yes, but…” or with a quizzical “in what way do you mean this?”  The mystery of the metaphor charms us into examining more closely what it is and how it fits into the context.  A metaphor engages us; it invites us to think about how different aspects of the metaphor can create new meaning and understanding of the situation.

Metaphors are ambiguous.  Through this ambiguity, they can provoke reflection, initiate discussions, and even provide a bridge to the unknown from something known.  At their best, metaphors help us make sense of new situations and gain insight about the nature of disruptive events and evolving situations.   

But at their worst, metaphors can constrain our thinking and limit our imagination.  Instead of magic and engagement, a metaphor can be a sleight of hand that focuses our attention away from the critical actions and significant issues.   This misdirection can happen implicitly without our awareness, as many metaphors have become so embedded in our discourse that we forget they are metaphors.  References to space and vision are particularly evident in our everyday research discussions:  I see what you mean [do we acknowledge that seeing is not comprehending?]; my area of research [deliberately bounding our interest and limiting our range of attention]; the information superhighway [directing us to consider that information and knowledge, as if they were in containers, move along predetermined paths]; etc. 

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The MakeR way: Using R to reify social media data via 3d printing

Posted by on Oct 3, 2013 in Data Visualization, Information Visualization, Methods, Modeling, R, r-project, Social Networks, Uncategorized | 6 comments

small_3dprintIf you’ve read any of my previous posts you know that I am constantly experimenting with different ways to represent and explore social network data with R. For example, in previous posts I’ve written about sonification of tweet data, animation of dynamic twitter networks, and various ways to plot social networks (here and here). In each case the underlying idea is finding different ways to explore data under the assumption that sometimes just looking at something from a different point of view reveals something novel. In this post I will briefly discuss how to go from data to 3D model network, to 3D object using R most of the way.

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The Era of Pretended Transparency

Posted by on Aug 28, 2013 in Transparency | 0 comments

Finally and for the first time, Facebook released a report that allegedly discloses the global government requests for data. The report details (among other things) the name of country, the number of requests and the percentage of disclosed data by Facebook.

Screen Shot 2013-08-27 at 5.54.41 PM

It is NICE that Facebook finally publishes a report about government data request. OK, it is important!

Google for example has been doing that regularly since 2009 with the Google Transparency Report. A report that is more detailed and gives more casino pa natet information (as it should) to users.


“Transparency and trust are core values at Facebook ”  the report says. But now after Snowden-Gate, we know that certain governments (say the US) have direct access to data from Facebook and other big companies.

Shouldn”t Facebook disclose information about this as well? How much data and what kind of data is extracted on a daily basis by governments (say the US)? Of course Facebook is not the issue. The same request can be made to Google, Yahoo, Apple, Microsoft or name it.

Publishing a report and pretending it is transparency, is a good way to mask relevant information that should be accessible to users.

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Data sonification with R: the sound of Twitter data

Posted by on May 29, 2013 in R, r-project, Social Networks | 2 comments

tweet_waveWhat does a tweet sound like? Not the kind that flies around in the air, but the kind that zips to and from our mobile devices. I’m intensely interested in finding ways to make sense of data. Sonification of data – representing data with sound – offers one way to do that. This post steps through R code to take the text of tweets and turn them into short chirping sounds. It also uses different tones for different users so that each user has a “voice”. In other words, this post shows how to use R to make Twitter data sing.

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Big Data Viz Rap: Visualize, Analyze and Realize

Posted by on Apr 12, 2013 in Data Visualization | 1 comment

DataVizRap_800x800Robert Mason, Shawn Walker and Jeff Hemsley participated in the University of Washington, Information School’s iAffiliates Day, “an event that fosters new partnerships and showcases the innovative work being done at the iSchool. The event is an unconference format with the theme of discovering information partnerships”. Participants give a two minute lightning talk intended to “enlighten, inspire, educate, or otherwise engage the audience” about a given topic. Jeff chose to “otherwise engage” the audience with a two minute rap about data visualization. Read more for the full text.

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