Social Networking – Page 6

Tropes vs. Women in Video Games

I’ve been meaning to write about sexism in games for a while, but today I came across a YouTube video essay More than a Damsel in a Dress: A Response by Commander Kite Tales. This a response to Damsel in Distress: Part 1 – Tropes vs Women in Video Games by Anita Sarkeesian.

But first, a bit of history.

On May 17th, 2012 Anita Sarkeesian launched a Kickstarter campaign to improve the Feminist Frequency video web series of essays on problematic gender representations. The first of the new series came out recently in March 7, 2013, Damsel in Distress: Part 1 – Tropes vs Women in Video Games. It is well worth watching.

Alas the campaign and Sarkeesian were attacked systematically; see, for a brutal example, the Amateur game invites player to beat up woman. The obscene and hateful attacks have been documented by columnists like Helen Lewis in the New Statesman article, This is what online harassment looks like. What did Sarkeesian do? Lewis puts it succinctly,

She’s somebody with a big online presence through her website, YouTube channel and social media use. All of that has been targeted by people who – and I can’t say this enough – didn’t like her asking for money to make feminist videos.

So why did all these trolls attack Sarkeesian? 4Chan seems to have been one site where they organized, but what bothered them so much about her campaign? Sarkeesian’s interpretation is that they made a game of harassing her. As she puts it, “in their mind they concocted this grand fiction in which they are the heroic players in a massively multiplayer online game…” She goes on to describe how the players of this “gamified misogyny” were mostly grown men, they used discussion boards as their home base for coordination and bragging, the setting of the game was the whole internet, and the goal was to silence the evil Sarkeesian to save gaming for men. The trolls would go out, harass her, and come back to their boards to show off what they had done. It was a particularly nasty example of an internet flash crowd organizing to silence a woman. It was also an example of how the internet can amplify behaviour and provide haven for misogynist communities.

Sarkeesian’s video essay wasn’t even an attack on men or games. It is clearly the work of someone who likes games but is critical of the repeated use of the “damesel in distress” plot device and other sexist crap. The video essay is, however, effective at challenging the uncritical consumption of cliched tropes in games using a medium commonly used in gamer culture (short video essays that show game play and comment on games.)

Now, back to More than a Damsel in a Dress: A Response which argues that Sarkeesian didn’t look at the evidence with an open mind and that the princess in distress in both the Mario and Zelda series of games should be seen as brave individuals dealing bravely with distress that also represent the peace of their kingdom. While I find Kite Tales’ argument somewhat sophistical and mostly answered already by Sarkeesian, we should probably welcome responses like those of Tale that don’t attack the messager, but try to respond to the argument in some fashion; and there are quite a few responses if you care to work through a lot of poor arguments. It would be nice to say that video essayists are modeling how a conversation on these issues should take place rather than hurl abuse, but the medium doesn’t really lend itself to conversation. Instead we have isolated video essays with lots of comments. Not exactly a dialogue, but better than abuse.

While I’m on this issue of damsel’s in distress like Princess Peach, Ars Technica has a story about how a Dad hacks Donkey Kong for his daughter; Pauline now saves Mario. Alas, it too got abusive comments, the worst of which have been compiled into YouTube Reacts to Donkey Kong: Pauline Edition. The compilation focuses on the sexist and homophobic comments. If you scroll through the comments now you will find that they are mostly supportive of the Dad. The good news seems to be that the sorts of comments Sarkeesian faced are being shamed down or being reflected back.

As for Anita Sarkeesian, her Kickstarter campaign raised much more than she asked for and she now has the funds and attention to do a whole series. I look forward to the next part on Damsel in Distress that promises to look at more contemporary games.

Using Zotero and TAPOR on the Old Bailey Proceedings

The Digging Into Data program commissioned CLIR (Council on Library and Information Resources) to study and report on the first round of the programme. The report includes case studies on the 8 initial projects including one on our Criminal Intent project that is titled Using Zotero and TAPOR on the Old Bailey Proceedings: Data Mining with Criminal Intent (DMCI). More interesting are some of the reflections on big data and research in the humanities that the authors make:

1. One Culture. As the title hints, one of the conclusions is that in digital research the lines between disciplines and sectors have been blurred to the point where it is more accurate to say there is one culture of e-research. This is obviously a play on C. P. Snow’s Two Cultures. In big data that two cultures of the science and humanities, which have been alienated from each other for a century or two, are now coming back together around big data.

Rather than working in silos bounded by disciplinary methods, participants in this project have created a single culture of e-research that encompasses what have been called the e-sciences as well as the digital humanities: not a choice between the scientific and humanistic visions of the world, but a coherent amalgam of people and organizations embracing both. (p. 1)

2. Collaborate. A clear message of the report is that to do this sort of e-research people need to learn to collaborate and by that they don’t just mean learning to get along. They mean deliberate collaboration that is managed. I know our team had to consciously develop patterns of collaboration to get things done across 3 countries and many more universities. It also means collaborating across disciplines and this is where the “one culture” of the report is aspirational – something the report both announces and encourages. Without saying so, the report also serves as a warning that we could end up with a different polarization just as the separation of scientific and humanistic culture is healed. We could end up with polarization between those who work on big data (of any sort) using computational techniques and those who work with theory and criticism in the small. We could find humanists and scientists who use statistical and empirical methods in one culture while humanists and scientists who use theory and modelling gather as a different culture. One culture always spawns two and so on.

3. Expand Concepts. The recommendations push the idea that all sorts of people/stakeholders need to expand their ideas about research. We need to expand our ideas about what constitutes research evidence, what constitutes research activity, what constitutes research deliverables and who should be doing research in what configurations. The humanities and other interpretative fields should stop thinking of research as a process that turns the reading of books and articles into the writing of more books and articles. The new scale of data calls for a new scale of concepts and a new scale of organization.

It is interesting how this report follows the creation of the Digging Into Data program. It is a validation of the act of creating the programme and creating it as it was. The funding agencies, led by Brett Bobley, ran a consultation and then gambled on a programme designed to encourage and foreground certain types of research. By and large their design had the effect they wanted. To some extent CLIR reports that research is becoming what Digging encouraged us to think it should be. Digging took seriously Greg Crane’s question, “what can you do with a million books”, but they abstracted it to “what can you do with gigabytes of data?” and created incentives (funding) to get us to come up with compelling examples, which in turn legitimize the program’s hypothesis that this is important.

In other words we should acknowledge and respect the politics of granting. Digging set out to create the conditions where a certain type of research thrived and got attention. The first round of the programme was, for this reason, widely advertised, heavily promoted, and now carefully studied and reported on. All the teams had to participate in a small conference in Washington that got significant press coverage. Digging is an example of how granting councils can be creative and change the research culture.

The Digging into Data Challenge presents us with a new paradigm: a digital ecology of data, algorithms, metadata, analytical and visualization tools, and new forms of scholarly expression that result from this research. The implications of these projects and their digital milieu for the economics and management of higher education, as well as for the practices of research, teaching, and learning, are profound, not only for researchers engaged in computationally intensive work but also for college and university administrations, scholarly societies, funding agencies, research libraries, academic publishers, and students. (p. 2)

The word “presents” can mean many things here. The new paradigm is both a creation of the programme and a result of changes in the research environment. The very presentation of research is changed by the scale of data. Visualizations replace quotations as the favored way into the data. And, of course, granting councils commission reports that re-present a heady mix of new paradigms and case studies.

Twitter hands your data to the highest bidder, but not to you

The Globe and Mail had a very interesting article on how Twitter hands your data to the highest bidder, but not to you. The article talks about how Twitter is archiving your data, selling it, but not letting you access your old tweets. The article mentions that DataSift is one company that has been licensed to mine the Twitter archives. DataSift presents itself as the “the world’s most powerful and scalable platform for managing large volumes of information from a variety of social data sources.” In effect they do real-time text analysis for industry. Here is what they say in What we do:

DataSift offers the most powerful and sophisticated tools for extracting value from Social Data. The amount of content that Internet users are creating and sharing through Social Media is exploding. DataSift offers the best tools for collecting, filtering and analyzing this data.

Social Data is more complicated to process and analyze because it is unstructured. DataSift’s platform has been built specifically to process large volumes of this unstructured data and derive value from it.

One thing that DataSift has is a curation language called CDSL (Curated Stream Definition Language) for querying the cloud of data they gather. The provide an example of what you can with it:

Here’s an example, just for illustration, of a complex filter that you could build with only four lines of CSDL code: imagine that you want to look at information from Twitter that mentions the iPad. Suppose you want to include content written in English or Spanish but exclude any other languages, select only content written within 100 kilometers of New York City, and exclude Tweets that have been retweeted fewer than five times. You can write that in just four lines of CSDL!

It would be interesting to develop an academic alternative similar to Archive-It, but for real-time social media tracking.

Whistleblower: The NSA is Lying–U.S. Government Has Copies of Most of Your Emails

According to National Security Agency (of the USA) whistleblower William Binney, the NSA probably has most of our email. See the video Whistleblower: The NSA is Lying–U.S. Government Has Copies of Most of Your Emails. The question then is what they are doing with it? He mentions that the email can be “put it into forms of graphing, which is building relationships or social networks for everybody, and then you watch it over time, you can build up knowledge about everyone in the country.” (see transcript on page). In other words they could (are) building a large social graph that they can use in various ways.

In the transcript of the longer video Binney talks about various programs developed to filter out all the information:

Well, it was called Thin Thread. I mean, Thin Thread was our—a test program that we set up to do that. By the way, I viewed it as we never had enough data, OK? We never got enough. It was never enough for us to work at, because I looked at velocity, variety and volume as all positive things. Volume meant you got more about your target. Velocity meant you got it faster. Variety meant you got more aspects. These were all positive things. All we had to do was to devise a way to use and utilize all of those inputs and be able to make sense of them, which is what we did.

Binney goes on to talk about the code named Stellar Wind program that Bush authorized and then was forced to change after a revolt of some sort in the Justice Department in 2004. Stories tell of senior Bush advisors trying to get Ashcroft to sign authorization papers for the program while he was in the hospital. As for Stellar Wind, it seems to be mostly about metadata – the date, to, and from of emails that you could use to build a diachronic social graph which is what Binney was talking about. Strictly speaking this would be social network analysis rather than text analysis, but they might have supplemented the system with some keyword capabilities. Another story from Time points out the problem with such analysis – that it generates too many vague false positives. “Leads from the Stellar Wind program were so vague and voluminous that field agents called them “Pizza Hut cases” — ostensibly suspicious calls that turned out to be takeout food orders.”

Either way, these hints give us a tantalizing view into how text and network analysis is being experimented with. Are there any useful research applications?