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There are some more simple network analysis, which I think are more user friendly (just one click :) ): Mentionmapp (http://mentionmapp.com/) and Vizify (https://www.vizify.com/yahoo#transition) can be used to analyze people's twitter network, and InMap (http://inmaps.linkedinlabs.com/) can be used to analyze people's professional network.

Nice summary of both advantages and disadvantages of dedoose. Although I have mentioned some points (e.g. cross-platform) during my presentation, there are some other features that I have not covered - the visualisation function and the issue of no local copy.

[Synopsis] This book is a critical and ethnographic study of camgirls: women who broadcast themselves over the web for the general public while trying to cultivate a measure of celebrity in the process. The book's over-arching question is, "What does it mean for feminists to speak about the personal as political in a networked society that encourages women to 'represent' through confession, celebrity, and sexual display, but punishes too much visibility with conservative censure and backlash?" The narrative follows that of the camgirl phenomenon, beginning with the earliest experiments in personal homecamming and ending with the newest forms of identity and community being articulated through social networking sites like Live Journal, YouTube, MySpace, and Facebook. It is grounded in interviews, performance analysis of events transpiring between camgirls and their viewers, and the author's own experiences as an ersatz camgirl while conducting the research.

This study (and its author) is mentioned in this week's reading 'Digital Ethnography : An Examination of the Use of New Technologies for Social Research' by Dhiraj Murthy. Dissertation Remarks and Synopsis (from Theresa Senft's website) http://www.terrisenft.net/diss/synopsis.php#remarks

From the website: "The Society for Visual Anthropology (SVA) is a section of the American Anthropological Association. We promote the study of visual representation and media. Both research methods and teaching strategies fall within the scope of the society. SVA members are involved in all aspects of production, dissemination, and analysis of visual forms. Works in film, video, photography, and computer-based multimedia explore signification, perception, and communication-in-context, as well as a multitude of other anthropological and ethnographic themes.The Society encourages the use of media, including still photography, film, video and non-camera generated images, in the recording of ethnographic, archaeological and other anthropological genres. Members examine how aspects of culture can be pictorially/visually interpreted and expressed, and how images can be understood as artifacts of culture.

This article is of interest (http://mappingonlinepublics.net/2012/04/27/twitter-and-disaster-resilience-lessons-from-qldfloods-and-eqnz/) I would be interested in taking the map of twitter usage or during as disaster and the doing ethnographic follow up after the factor the see how this resource was used. This might build a better picture of how to use social media during disasters/similar problems.

How very interesting. Could be a really valuable read. I'm very curious how their method/methodology changes from other content analysis work in online spaces. If they take into account the unique context of blog comments (trolls, etc.).

I really like this piece! I'm not super familiar with DML as a field, but the author's attention to the world-making capabilities (and not even capabilities - it's built in or "politically preloaded") of research methods. The post provides a clear defense against those who would argue that research is just objectively recording the world. At the same time, it doesn't slip into a poststructuralist wormhole about meaning. There's an attention to politics here that 's fruitful [Ah! but politics in general.. What are this author's projects' politics? What departmental/ disciplinary political fights shape the ground on which DML research takes place?]

I really like the concept of "scene," as it is applied here. The author uses it to mean the ways groups of people gather in clusters historically, emotionally, and physically. He argues the term avoids the "fetishiz­ing tendencies of subcultural theory". Does it, though? If mapping and analyzing subcultures brings with it a temptation to nail down hierarchies of taste cultures (as in - "my study of zine making shows this is a real zine, that is not" - a temptation that looms even bigger for those of us who try to study our own subcultures), how does scene help us avoid that? Might I be tempted to flash my knowledge of the scene/ being a scenester in ways that produce the same effect? The visualizations help map out the fluid connection between actors and organizations. Describing local fan communities as "a nexus of niches" is tremendously helpful. I'd be interested to see this kind of network analysis applied to online fandoms across platforms. Thinking about the graph though, I'm not sure I need it to understand what he found. It looks cool (and bonus - !science), but I could do just as well without it. If the graph isn't supporting the argument - what is it doing? Final note - I like the choice of the word "patronage" - it may capture something really interesting about the relational and inter-generational aspect of scenes!

this is all you really need to read (abstract/chapter intro...): New technologies represent a system of constraints and possibilities that constitute the foundation of new rhetorical spaces: the spheres of new communicative and persuasive procedures. Nowadays, urban planning has the chance to critically and rigorously experiment with these new spaces. It has the chance to transgress traditional representational codes and to expand its semantic horizons. This chapter portrays one such challenging exploration: the fecund crossroads between qualitative analytical approaches and digital languages within the planning field. It is a path that embraces diverse dimensions media and messages, analysis and rhetoric, ethics and aesthetics.

I only read the first 15 pages or so of this chapter through Google Books preview - but - I loved it. It's beautifully written (jargon-y at times, but it's good for the genre). Plus, it works as a manifesto for the kinds digital ethnographies I want to read/experience. The best part for me was the author's focus on "multi -sensory aesthetics" in digital ethnographies. It's worth a block quote: Understanding that reason doesn't produce the totality of our actions, to create real communicative space, and induce peoples to act it is not enough to "tell" rather it is s necessary to transfer energies, make sentiments, and emotions vibrate, awaken latent aspirations, knowledge and enrages, rediscovering the powerful role of artistic and poetic languages. It is necessary to focus on the cognitive and communicative performance of aestehec pleasure, a pleasure that is not an accessory but rather a central moment of very communicative process.

quite robust listing of issues, possibilities, pitfalls, and facets related to research through/on the Internet...as of 2008. No solutions offered nor is there much analysis; a primer with a good bibliography

This article is written from the computer science perspective on how social sciences are used to analyze Human-computer-interactions (HCI) and computer-supported cooperative work (CSCW). Tthis article is talking about how ethnomethodology can help computer scientist to design systems allowing people to interact in groups through technology and computer networking. The article is concern on people's behaviors that takes them to interact with the technology and how they do it, some of these points can be stretched and transfer to understanding the behaviors of individuals that interact in digital communities. It continues talking about the influence of the participant in the design of the technology, which brings to my mind the discussion about how the data gathering and "aggregation of information" shape the actions, the behaviors and the data available, which at the same time can dictate how the technology is been developed

yEd is a powerful desktop application that can be used to quickly and effectively generate high-quality diagrams. Create diagrams manually, or import your external data for analysis. Our automatic layout algorithms arrange even large data sets with just the press of a button.

I think this article is really spot on in providing an important model for empirically studying and representing the spread of ideas (or controversies) between media and how participatory and professional media influence one another. The fact that this article is written as much for academics as for activists is also exciting (and scary) to me, as a means of thinking about agenda-setting and influence. How might access to these tools help activist campaigns, and how might they swing back to challenge them? How can you really measure effect? "Even when we are able to access the data we need for analysis, interpretation is complicated by the specificity of individualized media experiences, where we've each curated our own individualized lists of sources on platforms like Twitter and Facebook. This can leave us with very different understandings of the day's news. Is it possible to speak meaningfully about a media agenda when agendas are set by individuals following a combination of friends and professional sources they've chosen to meet personal preferences and needs?"

I've heard great things about this tool from fellow grad students and profs. It'd be nice to get a quick overview of how to use it if possible...

For those who may want to gather some quick demographics about an area in the U.S., BAO a free App from ESRI is very useful. Below are some of the features the App offers. Use on iOS and Android smartphones and tablets. Get up-to-date facts, using the latest Esri Data, about prospective customers (e.g., age, income, education, home ownership, lifestyle, and spending habits). Compare one address against another or against the county, state or US. Analyze an area within one-mile of your location. Instantly determine if a location fits your needs with Smart Map. Share your facts with others via e-mail.

Analysis of 2.6 million tweets shows Twitter is adept at correcting misinformation - particularly if the claim is that a tiger is on the loose in Primrose Hill This Guardian piece is an interesting way to think of scraping Twitter to show how mis-information moves across time in periods of crisis. I was living in London during this time period, and it was really amazing how influential social media was in shaping people's perceptions of the riots.

Twitter maybe correcting misinformation when it comes to riot rumors but its doing nothing to stop storytelling. https://twitter.com/1014retold Buzzfeed compared it to a re-life Game of Thrones http://www.buzzfeed.com/lukebailey/this-live-tweeted-medieval-irish-war-is-the-real-game-of-thr

Overview web application, visual document mining