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Get Off Your Twitter

August 25th, 2017

Web Science, more so than many other disciplines of Computer Science, has a special focus on its humanist qualities – no surprise in that the Web is ultimately an instrument for human expression and cooperation. Naturally, lots of current research in Web Science centers on people and their patterns of behavior, making social media a potent source of data for this line of work.

 

Accordingly, much time has been devoted to analyzing social networks – perhaps to a fault. Much of the ACM’s Web Science ‘17 conference centered on social media; more specifically, Twitter. While it may sound harsh, the reality is that many of the papers presented at WebSci’17 could be reduced to the following pattern:

  1. There’s Lots of Political Polarization
  2. We Want to Explore the Political Landscape
  3. We Scraped Twitter
  4. We Ran (Sentiment Analysis/Mention Extraction/etc.)
  5. and We Found Out Something Interesting About the Political Landscape

Of the 57 submissions included in the WebSci’17 proceedings, 17 mention ‘Twitter’ or ‘tweet’ in the abstract or title; that’s about 3 out of every 10 submissions, including posters. By comparison, only seven mention Facebook, with some submissions mentioning both.

 

This isn’t to demean the quality or importance of such work; there’s a lot to be gained from using Twitter to understand the current political climate, as well as loosely quantifying cultural dynamics and understanding social networks. However, this isn’t the only topic in Web Science worth exploring, and Twitter certainly shouldn’t be the ultimate arbitrator of that discussion. While Twitter provides a potent means for understanding popular sentiment via a well-controlled dataset, it is still only a single service that attracts a certain type of user and is better for pithy sloganeering than it is for deep critical analysis, or any other form of expression that can’t be captured in 140 characters.

 

One of my fellow conference-goers also noticed this trend. During a talk on his submission to WebSci’17, Holge Holtzmann, a researcher from Germany working with Web archives, offered a truism that succinctly captures what I’m saying here: that Twitter ought not to be the only data source researchers are using when doing Web Science.

 

In fact, I would argue that Mr. Holtzmann’s focus, Web archives, could provide a much richer basis for testing our cultural hypotheses. While more old school, Web archives capture a much, much larger and more representative span of the Web from it’s inception to the dawn of social media than Twitter could ever hope to.

 

The winner for Best Paper speaks directly to the new possibilities offered by working with more diverse datasets. Applying a deep learning approach to Web archives, the authors examined the evolution of front-end Web design over the past two decades. Admittedly, I wasn’t blown away by their results; they claimed that their model had generated new Web pages in the style of different eras, but didn’t show an example, which was underwhelming. But that’s beside the point; the point is that this is a unique task which couldn’t be accomplished by leaning exclusively on Twitter or any other social media platform.

 

While I remain critical of the hyper-focus of the Web Science community on social media sites – and especially Twitter – as a seed for its work, I do admire the willingness to wade into cultural and other human-centric issues. This is a rare trait in technological disciplines in general, but especially fields of Computer Science; you’re far more likely to read about gains in deep reinforcement learning than you are to read about accommodating cultural differences in Web use (though these don’t necessarily exclude each other). To that point, the need to provide greater accessibility to the Web for disadvantaged groups and to preserve rapidly-disappearing Web content were widely noted, leaving me optimistic for the future of the field as a way of empowering everyone on the Web.

 

Now time to just wean ourselves off Twitter a bit…

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WebSci ’17

August 14th, 2017

The Web Science Conference was hosted by Rensselaer Polytechnic Institute this year. The Tetherless World Constellation was heavily involved in organizing the event and ensuring the conference ran smoothly.The venue for the conference was the Franklin Plaza in downtown Troy. It was a great venue, with a beautiful rooftop.

On 25th June, there were a set of workshops organized for the attendees. I was a student volunteer at the “Algorithm Mediated Online Information Access (AMOIA)” workshop. We started the day off with a set of talks. The common theme for these talks were to reduce the bias in services we use online. We then spent the next few hours in a discussion on the “Role of recommendation algorithms in online hoaxes and fake news.”

Prof. Peter Fox and Prof Deborah McGuinness, who were the Main Conference Chairs, kicked off the Conference on 26th June. Steffen Staab gave his keynote talk on “The Web We Want“.  After the keynote talk, we jumped right into a series of talks. A few topics caught my attention during each session. Venkata Rama Kiran Garimella’s talk on “The Effect of Collective Attention on Controversial Debates on Social Media” was very interesting, as was the talk on “Recommendations for groups in location-based social networks” by Fred Ayala. We ended the talks with a Panel disscussion on “The ethics of doing Web Science”. After the panel discussions, we headed to the roof for some dinner and the Web Science Poster Session. There were plenty of Posters at the session. Congrui Li and Spencer Norris from TWC presented their work at the poster session.

 

27th of June was the day of the conference I was most looking forward to, since they had a session on “Networks : Structure, Identifiers, Search”. I found all the talk presented here very fascinating and useful. Particularly the talk “Herirachichal Change Point Detection” and “Adaptive Edge Probing” by Yu Wang and Sucheta Soundarajan respectively. I plan to use the work they presented in one of my current research projects. At the end of the day on 27th June, the award for the papers and posters were presented. Helena Webb won the best paper award. She presented her work on “The ethical challenges of publishing Twitter data for research dissemination”. Venkata Garimella won the best student paper award. Tetherless’ own Spencer Norris won the best poster award.

On 28th June, we started the day of by giving a set of talks on the topic chosen for the Hackthon, “Network Analysis for Non-Social Data”. Here I presented my work on how Network Analysis techniques can be leveraged and applied in the field of Earth Science. After these talk, the hackathon presentations were made by the participants. At lunch , Ahmed Eliesh from TWC won first place in the Hackathon. After lunch, we had the last 2 sessions at WebSci ’17. In these talks, Shawn Jones’ talk present Yasmin Alnomany’s work on “Generating Stories from Archived Collections” and Helena Webb’s best paper winning talk on “The ethical challenges of publishing Twitter data for research dissemination” piqued my interest.

Overall, attending the web science conference was a very valuable experience for me. There was plenty to learn, lots of networking opportunities and a generally jovial atmosphere around the conference. Here’s Looking forward to the next year’s conference in Amsterdam.

 

 

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