#libspill – a visual analysis of political hashtag use

The following is a visual analysis of the use of the political hashtag #libspill in the hours prior, during and after  the leadership vote, which retained Australia’s 28th Prime Minister as the leader of the Liberal party. For those readers, like myself, who maintain only a general interest in Australian politics and do not participate in the daily public discourse facilitated by hashtags like #auspol, this handy translation of the leadership ‘spill’ into Game of Thrones terms is incredibly illuminating. Similarly enlightening are the visual representations of the algorithmic clusterings of Twitter discussions, generated by the open source plugin for MS Excel, NodeXL, which can be used to provide a simple, but powerful diagrammatic analysis of the relevant hashtag use.

The approach here is very small scale, and my research interest is in the use of NodeXL as an ‘off-the-shelf’ application that requires no programming, coding or specialist training. My view is that micro-public data, and its analysis and management, is an important digital literacy, or perhaps a ‘network literacy’, that should be at the disposal of every social media user. The set of competencies, encounters and experiences that make up digital and network literacies are an especially important part of the contemporary skill set that students pursuing a Media and Communication Studies degree need to be equipped with in order to contribute and participate successfully in relevant careers and interests. We are already seeing the use of NodeXL and other forms of networked data visualisation for political and media reporting, but for a much more comprehensive ‘big-data’ approach, however, I recommend the work of Axel Bruns, Jean Burgess and others.

 

Twitter hashtag #libspill February 9 - 10, 2015

Figure 1. Twitter hashtag #libspill February 9 – 10, 2015. See https://www.flickr.com/photos/crypticon/16485604801/ for the original size.

 

Figure 1. is the visualisation of a sample of 2000 tweets captured in the 24 hours from Monday February 9th at 8am, covering the duration of Twitter hashtag use prior and post the leadership vote. Each ‘node’ in the graph is an individual user who tweeted the hashtag #libspill, or is a follower of a user tweeting with the hashtag. NodeXL plots an edge (a blue line in this case) between two nodes if there is a relation in the form of a follow, reply or mention, and the software generates a visual representation of the hashtag use and the larger context of its Twitter network activity in the form of the graph.

The graph is prepared according to the methodology developed by Smith et al (2014), which identifies six clustering structures that are commonly observed in Twitter conversation and emerge because individuals selectively choose who to reply to and mention. Meaningful information can be determined from these graphs as they represent the expression of opinion, the citation of information sources, and the organisation of individuals into discrete micro-publics of follows and following, tweets, replies and mentions, and together these form the dynamic online conversation experience that is unique to the character limitations, tagging and other microblogging  practices of Twitter.

Smith et al’s methodology is intended to be expanded on by drawing on further qualitative and quantitative approaches, such as surveys, focus groups, one-to-one interviews, and the data gathered by NodeXL can be used in sentiment, discourse and content analysis. Even in simple everyday use, however, NodeXL can provide an immediate way into the Twitter data that is not immediately obvious from the flow of Tweets that traverse our mobile and desktop screens:

“Our approach combines analysis of the size and structure of the network and its sub-groups with analysis of the words, hashtags and URLs people use. Each person who contributes to a Twitter conversation is located in a specific position in the web of relationships among all participants in the conversation. Some people occupy rare positions in the network that suggest that they have special importance and power in the conversation”  (Smith et all 2014: 2).

The automated clustering algorithm options in NodeXL map the individual nodes according to the ways groups of users connect to one another, in this case placing people more connected to one another in different regions on the map. At first glance it appears that Figure 1. belongs to the Polarized Crowd network type, which is dominated by two dense and heavily oppositional groups. Polarized crowds are divisive, especially with regards to political topics and events, and they are characterised by very few connections between the groups, which indicates that members of different groups are not conversing, but ignoring one another and relying on alternative sources when discussing issues (Smith et al, 2014: 3).

A close look at the nodes in the large group on the right hand side of the graph shows the the primary group is made up of politically manifold personas; including former Australian Prime Minister, Julia Gillard, and Rupert Murdoch whose position in the graph is very close to Tony Abbott’s official Twitter handle, @TonyAbottMHR, which is presumably operated by a member of his staff given his recents comments of the value of social media as “electronic graffiti”.

Where the Polarized Crowds of network conversations indicates groups that are not connected by strong ties, the Tight Crowd network involves many connections between the dense networks of communities of Twitter users. The graph in Figure 1. is much closer to Tight Crowd structure in which individuals across the network are aware of each other and have conservations and exchange links and information. The large number of edges between the two dominant groups of users and the small number of isolates and less connected users in the lower right portion of the image, reveals the sharing of commons points of interest or significance, and a strong group of connections to others with similar interests.

The Tight Crowd networks in Figure 1. are “… composed of a few dense and densely interconnected groups where conversations sometime swirl around, involving different people at different times”  (Smith et al 2014: 21). In the Tight Crowd network, argues Smith et al,  there is no “other” group as is the case of the Polarized Crowd network. This is an encouraging view of Australian politics, which suggests more conversation, discussion and debate between the major political views of its Twitter users than is the case in the U.S. (see Himmelboim et al 2013).

NodeXl can be used to determine a number of important metrics from the Twitter data and meta-data of each tweet, including the most frequently linked to URLs and domains, hashtags, words, word pairs, replies to, mentions and Tweeters in the groups as shown in the following tables:

Top URLs in Tweet in Entire Graph

Entire Graph Count
http://bit.ly/1nAtjp1 81
http://ow.ly/IHut3 36
http://www.skynews.com.au/news/feature-2/2015/02/09/abbott-hits-record-low-in-poll.html 19
http://www.smh.com.au/federal-politics/political-news/doctors-speak-out-against-conditions-on-nauru-20150208-137xwd.html 19
http://bit.ly/Zde7WJ 18
http://ow.ly/IHttt 14
http://bit.ly/1C8OJQt 12
http://bit.ly/1M3vmxK 11
http://trib.al/70eV2r9 10
http://www.theaustralian.com.au/national-affairs/abbott-leadership-crisis-judgment-day-as-newspoll-shows-pm-losing-voters/story-fn59niix-1227212412293 9
Top Domains in Tweet in Entire Graph Entire Graph Count
bit.ly 143
com.au 122
ow.ly 88
trib.al 18
ab.co 16
theunaustralian.net 14
net.au 13
twitter.com 11
afr.com 8
yhoo.it 7
Top Hashtags in Tweet in Entire Graph Entire Graph Count
libspill 2066
auspol 763
abcnews24 83
abbott 68
itson 56
halftermtony 53
newspoll 39
imstickingwithtony 35
worstpmever 33
abbottspill 32
Top Words in Tweet in Entire Graph Entire Graph Count
libspill 1804
rt 1317
auspol 678
abbott 402
spill 196
tony 190
abcnews24 131
amp 126
pm 118
turnbull 117
Top Word Pairs in Tweet in Entire Graph Entire Graph Count
libspill,auspol 316
auspol,libspill 183
tony,abbott 103
auspol,oㄥo 71
rt,annabelcrabb 68
oㄥo,abcnews24 56
rt,otiose94 55
otiose94,libspill 52
libspill,abbott 48
cory,bernardi 47
Top Replied-To in Entire Graph Entire Graph Count
annabelcrabb 7
tonyabbottmhr 6
corybernardi 6
liberalaus 2
cinderella_oz 2
theage 2
rupertmurdoch 2
abcnews 2
mikecarlton01 2
latikambourke 2
Top Mentioned in Entire Graph Entire Graph Count
tonyabbottmhr 83
skynewsaust 81
annabelcrabb 77
abcnews24 69
otiose94 58
turnbullmalcolm 58
smh 57
corybernardi 50
david_speers 44
mscott 44
Top Tweeters in Entire Graph Entire Graph Count
mackaysuzie 323277
hanezawakirika 321744
asher_wolf 316316
micaelsilva 272311
molkstvtalk 254564
ashghebranious 243974
sirthomaswynne 238350
geoffrey_payne 235494
upulie 218775
hangormango

196213

Another method to expand the data collection and analsysis process is the use of commercial web-based services to collect and visualise Tweets. These sites vary in cost and sophistication, but I’ve found TweetArchivist to be a reliable and useful service to record every tweet/hashtag mention from keywords. The site provides simple but effective visuals, and the data can be exported as CSV files or PDF for later content analysis and further network visualisation with applications like Gephi.

The data collection from the archiving process included 22,624 tweets registering 109,013,514 impressions from February 9 8am to February 10 8am, 2015, and can be used to get a sense of the most frequent hashtag users, the distribution of the #libspill hashtag use in conversation in terms of the volume of Tweets over time, and using a range of factors including number of tweets, followers, retweets and replies to, we can review a measure of the ‘influence’ of Twitter accounts involved.

This is highly useful for those interested in #auspol and shows those media outlets with an active Twitter persona, and more easily observe the mixture of print and broadcast television news and entertainment organisations actively using Twitter. NodeXL makes it easier to dig further into this data and there is masses of detail to unpack and consider from these images and information. In the next update I plan to take a brief look at the use of the #ImstickingwithTony hashtag and a closer look at the role of #auspol in mediation of Australian political conversations.

persona studies

In preparation for the upcoming book on Persona Studies, and the M/C journal ‘persona’ edition I thought I would just share a couple of blog posts that all use the term ‘persona’ to talk about very different issues and concepts.

Persona 5 – a very popular Japanese game

Persona – the television show

Persona and Greek Theatre and Sound in Counselling

Persona in Design

Persona and Target Audience in Advertising

Persona and Dorothy Parker – a poem

Persona and Grief

“…interaction design is the highest form of creative expression…”

Checkout this wonderful TED talk by Museum of Modern Art senior curator of architecture and design, Paola Antonelli.

Antonelli complicates the ‘video games are not art’ debate with a new collection of 14 video games at MoMA that celebrate ‘interaction design’ as the “highest form of creative expression”.

The appeal of the collection, according to Antonelli, is the distance and shock between art and design when on display in a gallery setting that enables visitors to appreciate the implications of video games and their contribution to the wider importance and meaning of design and celebrates these objects as having a crucial cultural value and roles within our everyday lives.

I’d love to play them all, at MoMA.

was it really only 30 days?

It’s finally over, and what an epic month it has been, while the crowd funding campaign didn’t make the target to fund the Values of Play survey or PlayCache project, the Deakin and Pozible crowdfunding experiment has been a tremendous success. I’ll explain why, but first, a very big  thank you to all who pledged, messaged and contributed to the campaign.

Thank you to all my wonderful friends, family, peers, colleagues, students and all the new friends, contacts and campaign supporters who put their names to the project for your willingness to fund original research. Thanks to those who tweeted and re-tweeted project messages, and to those who posted, liked and shared the PlayCache Facebook page, which has attracted new friends and followers. I will be continuing the project from there and posting regularly.

A special thank you to Professor Deb Verhoeven, Chair in Media and Communication, whose initiative, direction and leadership has created new opportunities for those of us at Deakin. Thanks must also go to Matthew Benetti and the Pozible crew. I’m already a proud supporter of a number of projects and will continue to be an active Pozible pledger! Thank you to Professor Matthew Allen, Professor of Internet Studies and Head of the School of Communication and Creative Arts at Deakin for backing the crowdfunding initiative and trumpeting the call for support to the School.

We often learn as much from our failures as we do from our successes. One of my favourite definitions of a gamer comes from McKenzie Wark’s book Gamer Theory, in which he defines gamers as “those who come to an understanding through quantifiable failure”. As a games studies scholar with an interest in the ‘indie’ and independent production of games, it’s given me a unique insight into the types of challenges developers are currently wrestling with.

The coverage of the Pozible campaign by journalists and bloggers with an interest in games and the values of play, helping us work past the stereotypes, has been fantastic. It’s also been a great chance to participate in the debates across Facebook, Twitter and Reddit over the implications of crowdfunding research and what it means to the Australian University sector.

The campaign has enabled me to create new networks, contacts and opportunities, such as panel at the Human Rights Commission in Sydney next week, where I’ll be talking about Games and Human Rights (http://www.mcvpacific.com/news/read/australian-human-rights-commission-to-host-panel-on-human-rights-in-videogames/).

The attention from the Pozible experiment has also created a marvelous new opportunity for Media and Communication and Creative Arts students at Deakin and I’ll be working with student filmmakers and bloggers in a collaboration with Invest Victoria, the business and innovations promotions unit of the Victorian government to cover the PAXAustralia games convention in July (http://aus.paxsite.com/).

Please do consider pledging to James McCardles’s ‘Retake Melbourne’ Pozible campaign at http://www.pozible.com/project/22875 and Euan Ritchies ‘Discovering Papua New Guinea’s Mountain Mammals’ project at http://www.pozible.com/project/22847. Two great projects that definitely deserve our support.

Thanks again and play on!

 

E-sports and gamer persona

At one point StarCraft 2 player ‘Idra’ held one of the most lucrative sponsorship contracts in E-sports and a notoriety for trash talking and disdain for other players. His dismissal from the competitive SC2 team ‘Evil Geniuses’ sends an important message to high profile players about attention to their public persona, acceptable competitive behaviour and the messages they communicate to fan communities.

Serres, time travel and the Gothic in science fiction

Three new postgraduate students to co-supervise this year. The first I’ve caught up with so far is a Creative Arts students writing a science fiction novel. The exegesis for the thesis will focus on the Gothic in science fiction and to kick the process off, we will be working on an analysis of the Gothic in the Mass Effect series. The aim is to prepare an article for a games studies or the science fiction studies journal, and to contribute to the formation of an emerging research group on technology and science fiction studies at Deakin. In doing some fresh research I came across a great article by Laura Salisbury on Michel Serres, time travel and gothic SF. It’s a cracking read and coincides with the material I’m working on using Serres concept of quasi-objects to analyse the use of screenshots in participatory gamer cultures (to adopt Joost Raessen’s term).

seeing through Glass

It would take a lot for me to shift from my iPad mini to an Android tablet but Google Glass would do it. I’m scaling up the use of G+ in my teaching this year after a successful trial of the Hangout feature and live online tutorials via my laptop in the tutorial rooms in 2012. I’ve lived with my (various versions) of iPad since launch and it’s been a marvellous extension to my brain, making my life that much easier just by being able to walk away from the PC and the laptop to research, write, communicate and play anywhere. Google Glass would mean getting rid of the laptop in the classroom and to bring the students at work, travelling or  just sitting at home in their pajamas a better ‘live’ online tutorial experience. Give me fives sets of these and the kind of research I could accomplish with an invested student cohort would be really amazing.

screenshots as digital tools and media objects

Now that I’ve had a chance to properly experiment with the open source social network overview and exploration tool, NodeXL, I’m finally finding some traction. I’d  tinkered with the plugin in the past and more recently managed to spend some time acquitting myself with a little graph theory and social network analysis methodology. Together with an updated version of the software and the Hansen, Schneiderman, and Smith’s (2011) Analyzing Social Modeia Networks with NodeXL, I was ready to explore the use of screenshots in social media.

The approach in my postdoctoral study of ‘indie’ and independent cultures of games production in Australia has, until now, featured a purely ethnographic methodology; interviews, participation, observations and combinations of the three. It was quickly made obvious by the research participants, however, that one of the long term effects of the global financial crisis on the games industry is the intensification of the role of social media in games development at three distinct levels: as means for communicating with a diverse audience populations (an evolution of the more traditional marketing/broadcast model modified for social media); as tools for facilitating actual game development remotely (using Skype, Google Docs, Facebook,Twitter, etc); and as processes and practices for the knitting together of a global games community of developers, artists, players, etc that spans the mainstream, that provides indie and independent with a powerful (but not equal) means for gaining attention to their games. It is this last feature of social media technologies and their uses that contributes to changing conversation about play and games, and has even produced a few global celebrities, like Minecraft developer Notch.

The well established ties to the global console ports, movie tie-ins, mobile- and web-based games markets were already jeopardised prior to the GFC with the rising Australian dollar which made local development more costly. A series of major studio closures from 2010 meant the turn to the iOS and Android platforms for Australian developers was inevitable. In part as a reaction to the convergence of web and mobile markets through smartphone and tablet devices and also in part a reaction to the new digital and social tools available to developers. The new generation of young graduates from specialised games development courses have emerged to start competing with much more established studios and major IOS Australia studio success like Halfbrick and the Voxel Agents.

Although it’s only speculation at this point there are signs that the rise of the indie developer and the growth of the small independent studio developers means an overdue shift in the industry’s entrenched problem of diversification, with women being underrepresented in the Australian industry. One of the data sets I intend to look as part of this research is the recent use of Twitter hastag #1reasonwhy that has been increasing attention to the conditions women face working in the industry (if they can get hired in the first place). It is clear through observing the highly profitable and expanding market in games paratexts (including websites and merchandise, YouTube channels, blogs and podcasts) that we already seeing a significant change with many more women’s opinions, perspective and thoughts on games and games culture being seen and heard, and not just from so-called ‘gamer girls’ or Booth Babes at the latest convention.

As social media takes hold at all levels of games culture the digital literacies involved for the humanities researcher attempting to understand these changes takes on higher stakes at the level of cultural production of media objects, such as screenshots. Learning to use NodeXL means having to correct a number of deficiencies in my repertoire, including a lack of knowledge and expertise in using Excel, and coming to terms with the discourses and terminology of social network analysis and graph theory. By no means have I achieved an expert status, but I feel confident graduating from padawan, especially as I begin to dig into the analysis of the use of screenshots in social media. This research intersects with a personal hobby and helps me expand on the analysis of the digital objects (like virtual hats and game screenshots) that are used as a means for building a mediated online persona. By persona I don’t mean avatars or individual profiles, but a collective and identifiable online presence, one that is often text based – blogs, profiles,Steam and Xbox Live – with important visual components and aesthetics captured on PCs, mobile phones, laptops and tablets and shared via sites like Flickr and Facebook, Twitter, Reddit and YouTube.

I’ve put together a Flickr set for the purpose of demonstrating NodeXL here and will be updating the blog with results and discussion as I progress further.  Below is a graph of my core Flickr user network, grouped by relevant cluster, you can see my two accounts Crypticommonicon (for game screenshots) and Moorenet (the family photo album) and you can see the links to close friends and family in the boxes on the left then move across to contacts I have added to my follow list but who have not added me in return.

NodeXL Flickr User Network Map
This graph represents connections (contacts and comments) in my Flickr user network, as plotted by NodeXL, using the Harel-Koren Fast Multiscale algorithm. The layout is arranged with the group by cluster function according to the Girvan-Newman clustering algorithm. Duplicate edges are merged,  Edge Width and Visibility are mapped to Edge Weight. NodeXL Version 1.0.1.229