Because these accounts are of different ages, for some comparisons it is useful to look at the ratios, that is the statuses, followers, favorites etc on a per-day basis. There is still a potential bias here towards newer accounts, in that they are perhaps likely to be more active having recently decided to join the platform, so that is something to be aware of in viewing the data that follows.  In this post I do not intend to speculate too much on what the data means (excepting one specific example, which we will come to), as much of it needs further work to refine, however hopefully this first look at the data we are obtaining is interesting nonetheless.

Statuses Per Day

For each of the charts below, what is shown are the statuses per day for all accounts generated on a particular day. the volume of account registrations (which we estimated at 1 million IDs per 8 hours in a recent post) means that for the more recent datasets the data only covers accounts created over the period of a few days. In Tableau, these ratios are generated by the formula: ([statuses_count]/((**creation date**-([created_at]/1000))/84000)), where the creation date is the unix time at which the data was collected. Given that, at the time, this process took some hours to run, there is an element of imprecision here, however in the grand scheme of things the impact should be minimal.

Followers Per Day

These visualisations show an increased numbers of followers per day in new accounts, however that is to be expected given that there is a finite number of twitter users, and newer accounts will show an increased velocity of followers.

Followers Per Day (Less than 2000 – Excludes 13 accounts)

This is a slightly more interesting visualisation than the one above, as it excludes accounts including @BarackObama which heavily skewed the scale.  Highlighted here is that newer accounts often have a lower rate of followers/day than those a few months old. Also interesting is that a number of the early accounts maintain high followers/day ratio, which perhaps speaks largely to the identify of those early adopters, such as news organisations and Starbucks which was discussed in a previous post.

Friends Per Day

This data has a similar caveat to that given above, in that newer accounts are likely to follow more people in their early days than once the account has aged. Nonetheless, as with the followers chart above, the drop-off on the more recent accounts is interesting, which perhaps suggest that the following of large number of users is not an immediate process, but comes having established a presence on Twitter for a period of months.

Friends vs. Followers

Having established that baseline data, I also mapped these ratios against each other. For example, here is Followers per Day vs. Friends Per Day, colour-coded for data-set (the darker the colour the newer the account, the exact breakdown can be seen on the colour key). I’ve again cut out extremities in both the followers and friends count to show the majority of the user base:

Statuses vs. Favorites.

One of these charts stood out however, and sparked my interest for future work.  Anecdotally, several have commented on the recent increase of ‘favoriting’ on Twitter,  with some users appearing to adopt the feature as equivalent to the Facebook Like. The below chart, which shows Statuses Per Day graphed against Favorites per day shows an interesting pattern in the bottom left corner. In this chart, light blue is the ‘new data’ (11 million IDs from c. December ‘12), red are the ‘first million’ Ids, and brown are the ‘recent million’ (e.g. March ’13).

As you can see, there appear to be a significant number of users who favorite as many as 30 tweets a day, but don’t post new content; thus mimicking the ‘lurker’ behaviour identified on other platforms.  Additionally, the data may show a rise in favoriting, in that while there are a chunk of early users who are averaging over 10 favorites/day (and we can’t tell for sure whether this is a lot of favoriting recently or a steady rate over the years), amongst more recent users we are seeing favorite counts of up to 70/day, suggesting this may be a more recent phenomenon.

And, as the first chart above shows, there’s a lot more data to collect and analyse!

Overall Volume

This data represents tweets that contain Vine URL’s (i.e. match “vine.co”), and thus includes videos being posted to twitter, as well as replies and re-tweets that contain the URL. As you can see in the above diagram, tweets about vines have increased in volume significantly over the period (the final day represents incomplete data). From around 2000 vines per day on Twitter during the first few days of data collection, the final weekend (16/17 March) saw 6000-7000 tweets. There also appears to be weekly variation, in that weekends see more tweets posted than weekdays.

Daily Patterns

Taking a look at the first week of vines provides some more detail about the daily pattern observed above. On each day there is a sharp drop-off to a floor happening between 16:00 and 20:00 AEST, which is 1am – 5am US Eastern Time. The daily peaks vary from 1am and 12noon AEST, which is 10am and 9pm US Eastern. This would certainly suggest that Vine is currently very US-centric.

Some Metrics

Compared to other tweets we have investigated, tweets surrounding vines are fairly well distributed. Among over 1.5million tweets in this first months database, there were 441,091 individual users, so an average of just over 3 tweets per person. The top 1% by volume contains those with over 28 tweets, and is 195,280 of the total.

Across the whole user base, 74% of tweets are original (that is, are not either a retweet or a reply), 18.5% are retweets, and 7.5% replies. Among the 294,499 users who make up the lower 50% (between 1 and 3 tweets), the retweet percentage increases to 47.1% (with replies remaining similar at 8.8%), suggesting that these users are largely not part of the Vine community, but re-tweeting something from somebody they are following. The top 1% (4490 users), with more than 28 tweets, have 5.9% replies, and just 4.1% retweets, with over 90% of the tweets being original, suggesting that these users are the ones posting videos on a frequent basis. Those between 3 and 28 tweets similarly have 82% original tweets, so this grouping will capture those who have gone beyond simply a #firstpost with Vine.

Hashtags

615,830 of the 1.5million tweets contained a hashtag; encouraged by the Vine app to select tags which apply to their videos. While we want to conduct further, detailed, work to look at the content of the videos, the hash tags do provide us with a way to take an early look. Hashtags, unlike in our usual Twitter analysis, are not used in Vine to organize a conversation about a topic (although some may serve this purpose, such as #newsvine), but to enable people to find videos containing specific content, and indeed tags and user profiles are the only way to find videos through the Vine App.

Whilst the Vine App suggests hashtags, users are free to add their own, and as such there were 128,770 hashtags in the data set. The chart above shows the top 20. Notable is that #firstpost is included 21,276 times – this is the default hashtag in the Vine tutorial for a users initial video. Vine is also a common term (and our tools differentiate between upper and lower case, and so combined this gives 14,389 occurrences. SXSW is also prominent (in both capitalized and uncapitalized forms), with 10920 occurrences, which is obvious period specific. The other common hashtags, #cat, #cute, #dog, #favthings, #food, #funny, #howto, #magic, #music, #pets, #travel, and #vineportraits, give us an interesting first glance into uses of Vine.

Applications

No surprises here… the vast majority of these tweets come directly from the Vine application. Again this is filtered; the top 10 are displayed with those without a source excluded. The Twitter iPhone app is in second place and Twitter.com third. These would presumably be retweets and replies.

Popular Tweets

The above chart shows the 50 most popular re-tweets containing a vine URL during the past month. Those URL’s are reproduced below, so that you can check out the videos. The prominence of celebrities from other forms of media and marketing campaigns stands out amongst this selection.

text	Count
RT @DarrenCriss: My glee warm up to start the day. And intro to Vine. http://t.co/WSQom4BEAo	1,789
RT @VEVO_UK: Demi signs the VEVO wall http://t.co/zi6MJE4u	1,471
RT @fucktyler: WHERE IS IT http://t.co/6igl2EJCJ9	1,230
RT @fucktyler: SANDWHICHHH http://t.co/kgD9zYwYkX	1,132
RT @DarrenCriss: Me getting into Blaine mode. Wish it actually took this long. http://t.co/FzxpEAw5TN	1,113
RT @fucktyler: http://t.co/7HJFNdXGdP	1,005
RT @fucktyler: BURFDAY http://t.co/37ej09RQyv	998
RT @fucktyler: FAG http://t.co/A27rTa2sfn	884
RT @CostaCoffee: Have fun with Costa! #lovecosta http://t.co/PbFf5JXa	811
RT @fucktyler: http://t.co/aBBvlGz24t	753
RT @CostaCoffee: Sip like you mean it.. #lovecosta http://t.co/Ni6QuxvFRP	714
RT @CostaCoffee: Too many treats to choose from.. #lovecosta http://t.co/zKY2q05olf	696
RT @CostaCoffee: Made for loving you…. #lovecosta http://t.co/F8LG7EUJ	660
RT @fucktyler: Jasper http://t.co/jumrmjjlKp	640
RT @VEVO_UK: http://t.co/c5lKadbY	636
RT @fucktyler: PAUSE HAHA http://t.co/MAgSjzuPj6	619
RT @TeamMessi: …and here’s Leo signing them! Is this the worlds first #vine of Leo Messi? RT and follow to win. #askmessi https://t.co/TKYYsVUOoa	583
RT @markhoppus: Getting ready. http://t.co/5VlFbphB	544
RT @CostaCoffee: Hot chocolate‚ cream‚ marshmallows.. How do you have yours? #lovecosta http://t.co/RqdhyUbokw	507
RT @levvis_: me and harry styles and lily allen x http://t.co/2OBOEoPXXb	504
RT @markhoppus: Australia. http://t.co/KSFh0ZJI8k	493
RT @christoferdrew: photoshoot for sunflower http://t.co/tfI5kqt0Wy	485
RT @fucktyler: U FUCKED MY BITCH http://t.co/othkq6pCVB	473
RT @adidasUK: Follow @adidasUK & RT for the chance to win these signed boots by Gareth Bale! http://t.co/2EUtIhDV7v	457
RT @TeamMessi: …y aquí está Leo firmándolas! ¿Es este el primer #vine de Leo Messi? Haz RT y síguenos para ganarlas. #askmessi https://t.co/TKYYsVUOoa	450
RT @CostaCoffee: Made for loving you… #lovecosta http://t.co/F8LG7EUJ	448
RT @fucktyler: http://t.co/mHU19ePm7r	417
RT @GilletteUK: Gillette evolution. RT before 19/3 for your chance to WIN one of 5 ProGlide Silvertouch razors!! http://t.co/iFhSC2tvQK	413
RT @BrooklynNets: JOE JOHNSON DOES IT AGAIN! http://t.co/vsCLjWaU	403
RT @RouReynolds: nnnnnyehh http://t.co/GomLa8h5Ey	402
RT @Battlefield: Straight from the video editing suite: Prepare 4 Battle – 03.27! This sneak peek now‚ more soon. (Please RT!… http://t.co/CANw5vb9iW	398
RT @Lakers: That’s a W. #GoLakers http://t.co/mXhP7jZqyt	396
RT @louteasdale: Do something funny for money todaaaaay #comicrelief #halfbeard @benwinston http://t.co/8DFNd4zHkz	394
RT @aaronpaul_8: Every time I drink a coke this is how how feel during the act of drinking the coke. http://t.co/tqE08jmOTC	376
RT @Pysjamasgutten: Enkelte jenter ass http://t.co/rLVHUU6Jzf	351
RT @markhoppus: Happy Mother’s Day! http://t.co/c7FhBA8jWk	349
RT @fucktyler: 3 http://t.co/jC2M96qarZ	338
RT @coldplay: #MXcomic #issue1 A http://t.co/19DrcnOU9R	334
RT @fucktyler: Hahaha http://t.co/MnkTvtkx80	324
RT @markhoppus: Tour life. http://t.co/66tcJAWCG3	317
RT @ashleydzerigian: Love in the elevator! @keisharenee @rickjordandrums @adamlambert @whoisjohnnyrice @tommyjoeratliff @lovemysp… http://t.co/EZW8RvA1py	308
RT @MTVteenwolf: #83Days http://t.co/Dr8OUErBkj	303
RT @nikosofficiel: #mattpokora ou pas? @mpofficial http://t.co/4m9VTlfeoh	289
RT @rekorderlig: Follow and RT for the chance to win this Winter Cider set #beautifullyswedish http://t.co/lecrOKJezu	288
RT @JaredLeto: Del nuevo video de #MARS: Saludaste a Winston? https://t.co/GbedbZIO0i	267
RT @fucktyler: http://t.co/mc2OUYG8KC	262
RT @JaredLeto: RT @30SECONDSTOMARS #MARSisCOMING http://t.co/hcFy9Ktt	257
RT @GilletteUK: Gillette evolution. RT before 19/3 for your chance to WIN one of 5 ProGlide Silvertouch razors! http://t.co/iFhSC2tvQK	207

So that’s an early look at Vines; I expect to update once more on Vines before I head off on conference travels in early May, and a post on Twitter ratios will also be coming next week.

When did they join?

As you can see from the above graph, which shows Account creation date along the horizontal and ID along the vertical, a spattering of accounts were registered from late March to July 2006, with the first at approximately 20:50 on 21 March, ID#12. It is worth mentioning here that these are only accounts that are still active, and so it is impossible to access data for those which are no longer active. A slight increase in the registration rate of users occurred between November and December 2006, while late December ‘06 to early January ‘07 saw a sharp increase, corresponding to US publicity, which tapered off to a steadier rate until March ‘07 at which point we see a second publicity driven spike which took the IDs over the 1 million range. It is worth noting that of these 1 million IDs, only 48,546 accounts remain active.

Where in the world (is Twitter user x)?

This map contains some of the limitations discussed on Friday; namely that it is created by time zone, although interestingly does not show the same bias toward alphabetically prominent time zones such as Amsterdam as is present with new users. Also interesting here is the prominence of Italy, with about 4% of the active accounts coming from Italy, far higher than any non-English speaking country, and higher than Australia. The US is dominant, with well over 50%, however the neighbour to the north, Canada, accounts for only 0.3%, again a sharp contrast to the newly created data. Other hotbeds of early Twitter activity (those with over 1,000 of the 40,000 accounts) are limited to Australia and the United Kingdom.

What have they been up to since 2006?

The above chart shows total statuses posted, and shows some interesting patterns; whilst there are a few users with 400,000 plus tweets, the majority have managed to restrict themselves to 200,000 or less across the past 7 years, with the majority clustered below 50k. As we saw with the join times graph previously, there are a number of missing IDs (and thus 0 statuses) around the middle of the chart. The below chart, in which users are placed into ‘bins’ of 100,000 IDs again shows a fairly average status count among the users, suggesting that those early users whose account is still active (i.e. hasn’t been deleted) have tweeted more-or-less the same number of times as those joining during one of the publicity cycles.

Followers and Followees

Here, I have removed eight data points from the visualisation, which shows the numbers of followers by account ID; users with 29.3m (Barack Obama), 16.5m (Twitter themselves), 7.67million (New York Times), 7.5 million (CNN), 3.5 million (Starbucks), 3.2 million (BBC World), 3.17m (Mashable) and 2.6m (TechCrunch) followers. One random note from removing these is that Twitter themselves have an ID in the 783,000 range, while Starbucks are in the 31,000 range – clearly an early priority of the Twitter developers was not to create a corporate identity for themselves!

Again, we see a large number of IDs in the centre of the graph with little activity, replicating previous data, with two more populous clusters to either side. Here though, the later users show a marked increase in connectedness over those on the left side of the graph. The very early adopters (perhaps those who were in some way connected to a member of the development team), while tweeting regularly, may then be less connected than those tech aficionados who joined during the early phase of publicity.

The above diagram shows the number of accounts a user is following. Here, two accounts have been cut from this diagram for visualisation purposes; one following 665,279 users (Barack Obama) and the other 229,915. Otherwise, we see a fairly similar pattern as with statuses and followers, the missing IDs in the middle, with users to the left and right having fairly similar distributions to the followers graph above, re-enforcing the suggestion that later IDs seem to be more connected than the early users.

Overall then, an interesting distribution of early Twitter uses, which is in some ways similar and some ways different from the more recent users discussed on Friday. Now just to fill in the missing hundreds of million!

Registration Engines?

Firstly, I should mention that the above diagram, and all the others in this blog post, are from Tableau rather than Excel, which we are beginning to use for our analysis. The above graph has Twitter ID on the vertical axis, and Time Created on the horizontal, covering the full range of 1 million IDs and just over 8 hours. As you can see, accounts are being allocated in a more or less linear fashion (implying that old, deleted, account IDs are not recycled), but there appears to be a slight disconnect, in that at the same time account IDs are being allocated in two different ranges. In fact, as you can see by zooming in, there are actually 3..

This graph zooms in on a smaller period of time, between approximately 6:55 and 7:30pm UTC on 18 March. By zooming in, we can see that there are three approximately parallel lines, with the bottom one being out of sync from the top 2 by almost 2000 IDs, or about 11.5 minutes. One idea for the cause of is that Twitter has three separate registration engines allocating IDs, with each engine being allocated a range of IDs periodically, however we are unable to currently verify this; it could also be that there is some caching process before new accounts are added to the database.

It is also worth noting that of these 1 million IDs, there are 1762 accounts for which the API returns profile information, but have no username. One current theory is that these may be deleted and/or banned accounts in which the username is freed for re-use, but Twitter keep the account ID active for internal recordkeeping, however again further work needs to be conducted to confirm this. Given that there were a few days between the accounts being created and the data being collected, 1762 would seem a more reasonable number than 600,000 for banned accounts.

Where are they?

One advantage of Tableau is that it allows us to produce ‘easy’ visualisations of where in the world Twitter users are. There are a couple of different ways of doing this, and they all rely on users volunteering correct information. Of the 422,794 new users, 7,461 had geo-location enabled. A map of these users can be seen below, and this provides a relatively precise measure of the location of these users. What is interesting here, particularly in reference to the diagram that follows, is that both Russia and Canada have virtually no users with geo-location, yet both have a quite substantial number of overall users. By contrast, geo-located users are more concentrated in the United States and Europe, and Mexico and South America are also strongly represented.

The second technique we used was to map the users approximate location according to the timezone set in their user profile. As it turned out, this was a relatively tedious process of mapping Twitter timezones (which use a variation of time zone (‘Eastern time’, ‘Pacific Time’), City (‘Melbourne’) and Country (‘Greenland’)). In case anyone repeats that same exercise in the future, I have made a spreadsheet of the conversion available here, which you should be able to import into Tableau in CSV format. There are a few caveats with this data; countries such as The Netherlands and Morocco seem to be over-represented, which we believe to be caused by them being the first available location for popular timezones; for example Amsterdam is the first listed alphabetically for Central European Time, which includes populous countries such as France and Germany. This data also shows large numbers of registrations for the United States and Brazil. It is also worth mentioning that the time span here, approximately 4pm – 1am UTC, would be afternoon and evening in Europe, and noon-9pm in the US, while being late night and early morning in Australia, which may explain the low number of Australians in the dataset.

What do they do?

The three charts below show number of statuses, followers, and following respectively for these users a few days after their account was created. These more or less stand alone, however it is worth noting that for the chart showing total followers I removed 5 data points for the visualisation – these appeared to be accounts of celebrities, and had 75k, 32.5k, 24.9k, 24.5k and 17.5k followers.

Status Count vs. Date of Account Creation:

Followers Count vs. Date of Account Creation (note previous caveat):

‘Following’ Count vs. Date of Account Creation:

So, that’s who’s joining Twitter — now to think about the 25.2million new accounts that may have been created by the time this post goes live..

Subgroup: How/Why/For what are social media used in politics?

Most of the articles that mentioned user groups also gave an indication of why and for what these tools were used. In total, 30 out of the 56 articles we analysed discussed different uses of social media as political tools. This makes it the most discussed topic out of all of the categories we identified in our analysis. The chart below provides an overview of the 13 types of uses the articles we studied mentioned and the number of articles that cited these uses.

Using social media as a tool for interaction or online debate, as a means for politicians to create personal connections with voters, to create a personable image and to reach voters were the most commonly mentioned uses of social media in politics. It is noteworthy that all of these uses refer to how politicians use social media tools, not the public or journalists. This is in line with our previous finding that most of the articles that looked at user groups referred to politicians. Another well-represented reason why people use social media as political tools was to cut out the traditional media as a mediator between politicians and the public. The fact that this is a desirable quality of social media is revealing, in light of our interest in understanding how social media and traditional media interact. It seems that both politicians and the public see merit in a use of social media that sets them apart from traditional journalistic formats as mediators of political messages. It would be interesting to utilise sentiment analysis to tease out how newspapers react to and portray this kind of information that puts in question their authority as transmitters of political news and mediators between politicians and the public.

Some final words on the study and future plans

This was only a small-scale sample of what can be done, and the results I covered in this series of three blog posts only provide some preliminary insights into the representation of social media as political tools in traditional media outlets. In the future we seek to repeat the study on a larger scale with a more even distribution of articles across the years, and clearer limitations on which sources we obtain the articles for analysis from. Already, another more specific search has been performed on the Australia/New Zealand Reference Centre database, using the search terms polit* AND Twitter OR Tweet* OR Social Media OR Facebook. The publications were strictly limited to domestic news sources and these were then limited down further to 11 outlets (including the AAP and ABC News) that were deemed most relevant. We also decided it would be useful (and in the interest of limiting amounts of data so as not to end up with unmanageable results) to analyse articles by year and then compare them. At the moment we are thinking of searching for articles from 2008, 2010 and 2012 and perhaps 2013, and comparing across these years. The years were chosen because they represent important political events (2010 and 2013 federal elections) and a logical succession. 2008 was chosen because Twitter was in its infancy then and it will be interesting to compare how the perception of it as a political tool has changed between then and today. In order to further keep in check the amount of articles generated over such long periods of time, we have decided to look at articles only from the first week of every month of each year. An initial search for articles from 2012 resulted in 114 articles, which we will now analyse. To further facilitate our research, we are hoping to employ partially automated content-analysis via WordStat in our future analyses, in addition to manual readings.

Subgroup: User Groups

One of the subgroups of themes we identified in our content analysis of newspaper articles that reported on the use of new media as political tools was user groups. We noticed there were nuances between the ways in which the articles discussed how and by whom these tools were employed in the context of political practices. Most of the articles we analysed focused on the use of social media by politicians, some analysed their use by citizens as tools for political engagement, and others discussed how journalists employed social media as means of political news reporting.

Out of the total 56 articles we analysed, 19 referred only to politicians and how they use social media, 2 discussed just how the public engage with social media as political tools, and 1 mentioned only journalists as users of social media for political reporting. 3 articles referred to all three user groups, 11 articles mentioned politicians and the public, 2 mentioned politicians and journalists, and 2 mentioned the public and journalists.

Politicians were the most widely mentioned user group. The way in which politicians employ social media for campaigning and engaging with the public seems to be high up on the agenda in traditional news reporting on new media as political tools. Politicians are highly scrutinised, and often criticised, for their use of social media. For instance, 10 articles indicated that the social media practice of Australian politicians was unsatisfactory. One article in The Sydney Morning Herald from 2010 quotes a public relations expert who says that “The politicians aren’t using it [Twitter] themselves. They don’t understand it… All in all it’s a massive missed opportunity”. Another article in the Gold Coast Bulletin (2010) refers specifically to opposition leader Tony Abbott’s use of Twitter, saying that “it is clear he is far from understanding the medium”. The bulk of these 10 articles comes from the years 2010 (4) and 2012 (5). While, bearing in mind the uneven distribution of articles across publication years (see a previous blog post on this here), this does seem to indicate that criticisms and concerns around the use of social media by politicians flare up in the media around election times, when politicians are campaigning and being scrutinised for their practices.

About half of the articles that discussed politicians’ use of new media as political tools also referred to how everyday individuals use new media in connection to politics. The bulk of these articles refer to a politically engaged public that employs social media tools to talk about and make sense of political issues, as well as to seek a rapport with the politicians that represent it. Commonly, these articles lament that politicians are not making use of the two-way communication opportunities that tools like Twitter afford, leaving members of the public demanding more direct interaction with politicians. Fewer articles presented a more critical view of the public’s use of new media as political tools, one from 2012 suggesting, for example, that ‘Twitter is used by a tiny minority of people interested in the national political debate’. This leads to another popular point of discussion raised with regards to the everyday individual as a user of social media for political purposes, namely the demographics that limit which kind of users actually engage with politics through these tools. Another 2010 article confirmed that it is generally an educated and already politically engaged minority of urban professionals aged 25-34 that uses social media for political engagement. There were some discrepancies in terms of suggestions about gendered use of social media tools, some suggesting that the Australian blogosphere is dominated by males, whereas others reported on the growing female user base of many social media tools.

Out of the 8 articles that discussed how journalists use new media as political tools, all but one also referred to other user groups and made connections between them. These articles discussed how journalists, the public and politicians are either rival sources, or informants for one another, in terms of political information dissemination. For example, a publication on the AAP Australian National Newswire (2012) notes that ‘Sydney Morning Herald chief political reporter Phillip Coorey was the first to tweet an unofficial result’ in Labor’s leadership ballot that saw Julia Gillard replace Kevin Rudd as Prime Minister. It suggests that this ‘led to a flood of tweets from journalists, news websites and political junkies’ circulating information between one another, before the official result was actually announced. Griffin (2012, in a book review of Greg Jericho’s The Rise of the Fifth Estate: Social Media and Blogging in Australian Politics) suggested that there is a conflict between public actors, who are becoming increasingly involved as citizen journalists, and traditional journalists, as the experts on live reporting and analysis. The article discussed how Jericho queries whether the former are challenging the latter or whether there are still differences in news reporting by citizens and journalists.

The way in which traditional media report on the different user groups of new media as political tools provides an insight into the complex interrelations, conflicts of interest and mixed abilities of different user groups of social media. Politicians, citizens and journalists all have the opportunity to use these tools for political engagement. They have different agendas to follow and varying levels of ability in how they employ these tools for their purposes. From our initial content-analysis of 56 articles it became clear that politicians are the most scrutinised in terms of their use of these tools. Interesting issues around the demographics of citizen users who make use of new media for political purposes emerged, as well as indications of conflicts between these new citizen journalists and the traditional reporters who work for established media outlets. These are all themes to consider and follow up with further in-depth studies in order to gain an understanding of the use of social media in politics and the representation of this activity in traditional media outlets.

In the next and final post of this series I will take a closer look at the different uses of these tools in order to discern how, why and for what different users employ new media as political tools.

Our initial qualitative study of how new media are portrayed as political tools in traditional media outlets is a starting point for some of this research. In this post I will provide a brief overview of the study and an insight into one of the themes that emerged from our content-analysis, namely how social media and traditional media are compared and contrasted in the publications we explored. Future posts will explore further themes, such as how different user groups are portrayed and how, why and for what purposes they employ new media tools in connection to politics.

Data Collection

Publications

We performed an in-depth content analysis of a total of 56 articles generated through a combination of searches through the EBSCOhost database on the terms ‘Twitter’, ‘Facebook’, ‘social media’, ‘politics’ and ‘Australia’. The relevant articles were sourced mainly from Australian newspapers, predominantly The Sydney Morning Herald, The Age, The Australian and The Sunday Age, as well as other domestic papers. We also included results from the AAP Australian National Newswire, as well as a few transcripts of established Australian political TV programmes like ABC’s The World Today and Lateline that were sourced via the ABC Premium News service. Furthermore, we analysed four relevant articles from IT magazine Computer World.

For the purposes of future studies it may be worth considering whether or not television and magazine publications should be included in these searches at all, and if so, whether they should be explored separately or in combination with newspapers. Articles from an IT magazine like Computer World may not be representative of the general attitudes of traditional media outlets to new media as political tools. For the purposes of a first ‘quick and dirty’ analysis (a term borrowed from our current vising scholar, Jakob Linaa Jensen from Aarhus University), we considered these sources, as television and magazine journalism represent established media outlets through which political information is reported, and therefore can form part of an exploration of the portrayal of social media as political tools in traditional media.

Timeframe

The articles analysed in this sample were all published between 2008 and 2013. The graph below portrays the distribution of articles across the six years:

The bulk of the articles in the sample were published from 2012 onwards. This is indicative of the growing incorporation of the use of social media tools into everyday life. Already in the first two months of 2013, more articles were published (that were analysed in this study) than in the entire year 2011. The comparatively large number of articles that reported on social media and politics in 2010 is most likely attributable to the fact that the federal election was held that year. The election has commonly been referred to as the first ‘Twitter election’, due to the role social media were seen to have played in it. Bruns and Burgess have however pointed out that it was not so much the use of social media by politicians for campaigning purposes, but more the increase in engagement with political themes and discussions by the Australian public and news reporters that was noteworthy. As social media become more and more used, and as the next Australian federal election is imminent, the increase in reports on the political uses of social media in traditional media outlets is hardly surprising.

Analysis of the Data

Categories, Subthemes and Subgroups

We performed a close qualitative analysis of the 56 articles that mentioned social media and politics. From this in-depth reading we were able to identify particular themes and types of information, by which we classified the content of the articles and the way in which social media are talked about in traditional media outlets in connection to politics. We generated 19 main categories, some of which had subthemes. We grouped the 19 categories into 7 subgroups: Social media as political tools; Comparison between social media and traditional media; Nature of political discussion online; Comparison to other countries’ use of social media in politics; How/Why/For what are social media used in politics?; User groups; and Attitudes of user groups to social media. I will not list all of the categories and subcategories here, but rather proceed to discuss some of the insights we were able to draw from our analysis.

Identifying subgroups provided an insight into different aspects of the role of social media as political tools and into how this topic is portrayed in traditional media outlets. The subgroups we established reflect that some articles examine how social media themselves act as tools for political campaigning and/or engagement and/or reporting. Accordingly, different articles also report on different groups of users of social media as political tools – is it politicians using them? The general public? Journalists? And then how and for what do they use them? To engage voters? To become involved in political discussion? As a source for news reporting? Other articles are more concerned with comparing and contrasting social media and traditional media in their use as political tools – which is a more useful and/or more used medium? Again, distinctions have to be made between articles that report on different groups of users that employ these media and articles that discuss for whom these tools are useful/not useful. Some articles also draw comparisons between how social media have been used in politics in different countries, most commonly referring to the U.S. and occasionally to Britain. A further aspect explored by some articles are attitudes of different user groups (politicians, the general public, journalists, academics) to the usefulness of social media as political tools, as well as the nature of the political discussion online – is it more aggressive than offline debates? Does it trivialise political themes? Are things taken out of context and thus misrepresented?

This multifaceted array of themes indicated that there are many different aspects to be considered in understanding the role of new media in politics and their portrayal in traditional media. I’ll provide a closer look at one of the subgroups we identified, with further ones to follow in upcoming blog posts.

Subgroup: Comparison between Social Media and Traditional Media

28 out of the total 56 articles we analysed drew comparisons between social media and traditional media and made arguments about which were more useful/more used. Some articles of course portrayed multiple positions and did not always defend only one standpoint. Sometimes they reported on different opinions held by different user groups (politicians, the public, journalists, academics) rather than pushing one particular agenda.

It is interesting to note that all of the articles that suggested that traditional media were a more useful or more used political tool were published in 2010. Those that suggest that there is an interrelation between social media and traditional media in political news reporting, campaigning and engagement were largely from 2012 and 2013 (9 out of 13). Articles that suggested that social media were the more useful/used tool were a little more evenly spread across the publication years. These data have been represented in the graph below. While we have to bear in mind the uneven distribution of articles across years of publication (there were significantly more articles from 2010 and 2012 than from other years in the sample analysed in this study), we can infer that back in 2010, when social media were still less integrated into the processes of daily life, traditional media were still perceived to be more useful political tools. The increasing integration of new media into more and more aspects of our day-to-day lives is mirrored in the way in which traditional media sources report on their use in political contexts over time.

Our research theoretically permits an analysis of whether certain newspapers generally support a certain standpoint with regards to which are more useful tools in politics – social media or traditional media. While no representative results were discovered in this initial study, repeating this study on a larger scale and with a more even distribution of articles across newspapers and time periods, it may be discernible whether certain outlets have certain leanings.

So, to conclude, what we can infer from these preliminary findings is that in times of political action (such as around elections) the media report more on the use of social media as political tools (as suggested by the large number of articles represented in this study from years when federal elections were held in Australia). Social media are becoming more and more used in political practices and increasingly being perceived as either more useful than traditional media or as important interrelated tools that provide additional means of engaging with politics. It is important to note, and critically explore, these changes, not to make judgements about which medium is superior, but to gain a comprehensive understanding of the changing media landscape and how it is involved in shaping the social, cultural and political realities of our day-to-day lives. It will be interesting to see how these trends develop in light of the upcoming Australian federal election, and to compare them with the other countries involved in research projects in progress here at the CCI.

Check back for further posts on how different user groups were portrayed in the analysed articles (politicians, public, journalists), and how, why, and for what these different user groups employed social media tools for political purposes.

Standard background information: this analysis is based on tracking all tweets which contain links pointing to the URLs of a large selection of leading Australian news and opinion sites (even if those links have been shortened at some point). Datasets for those sites which cover more than just news and opinion (abc.net.au, sbs.com.au, ninemsn.com.au) are filtered to exclude irrelevant sections of those sites (e.g. abc.net.au/tv, catchup.ninemsn.com.au). For our analysis of ‘opinion’ link sharing, we include only those sub-sections of mainstream sites which contain opinion and commentary (e.g. abc.net.au/unleashed, articles on theaustralian.com.au which include ‘/opinion’ in the URL), and compare them with dedicated opinion and commentary sites.

See the posts tagged ‘ATNIX’ on this site for a full collection of previous results.

ATNIX Weeks 10-11/2013: 4-17 Mar. 2013

As this is another two-week update, I’ll begin with the week-to-week figures on link sharing for our basket of Australian sites. For the most part, sharing activity for the news sites has been steady – but this also means that the ABC’s historically unusual lead over the Sydney Morning Herald continues for a sixth and seventh straight week, for no real reason that I can identify. It’s not that the SMH is doing so poorly – since we started ATNIX in mid-2012, it’s usually tracked in the 25,000-30,000 tweeted links/week band, much as it is now. But so had ABC News – and that site has now surged ahead to remain steadily above 30,000 tweets, usually by some margin.

As we move to the opinion and commentary sites and sections, I need to make a correction first: in my last ATNIX update, I didn’t pick up on the fact that since 24 February, the Fairfax sites have now bifurcated their opinion sections into ‘opinion’ (by staff writers) and ‘comment’ (by members of the public). These exist under different site paths (e.g. smh.com.au/opinion vs. smh.com.au/comment). From now on, we’ll count tweeted links to articles under both these paths to the opinion and commentary link sharing total for Fairfax publications.

Even with the ‘comment’ links now added to the total, though, the two Fairfax flagships are faring comparatively poorly in this count, too. There’s a notable drop for the SMH and Age opinion sections over the past couple of weeks, allowing The Conversation to regain its traditional place as the second most linked to opinion site in the Australian media landscape, and to even put up a credible challenge for first place. It will be fascinating to see whether and how the gradual roll-out of Fairfax’s paywall access system (which comes online for overseas readers next week, as Mumbrella reports) will further affect these trends. (We did see a marked effect of The Australian’s paywall when it was switched on for opinion articles in October 2011.)

The day-to-day link sharing patterns bear out these differences in the relative performance of our news sites in even greater detail. Except for the weekends (when the newspapers’ specially targetted weekend reading features boost their numbers), the ABC outperforms its competitors by some margin; on an average day, it is usually linked to in tweets at least 1,000 times more than its nearest competitor, the Sydney Morning Herald.

Over the course of week 10, some of its most widely tweeted articles referred to the gunman in Brisbane’s Queen St Mall (370 tweets), Ted Baillieu’s resignation as Premier of Victoria (260 tweets), Julia Baird’s piece on International Women’s Day (220 tweets), and claims of policy brutality at the Sydney Mardi Gras parade (220 tweets) – a useful reminder, perhaps, that breaking news and controversial topics appear to have especially strong resonance on Twitter.

During week 11, the ABC’s three most tweeted news stories covered the attempts to de-extinct the gastric brooding frog, a story so strange that I’m willing to bet it also received plenty of tweets from outside of Australia (360 tweets in total), the subpoena of a Fairfax journalist as part of Gina Rinehart’s ongoing court battle with her children (interestingly, here it’s a news video sans accompanying text which received some 300 tweets), and the passing of the federal government’s National Disability Insurance Scheme by the House of Representatives (280 tweets). (As there weren’t any particularly major spikes in news activity during these two weeks, I won’t go into further detail for the other leading sites.)

As usual, opinion and commentary sharing is somewhat more fluid across the two weeks: here, it’s the Sydney Morning Herald and The Conversation which are battling for supremacy, while in week 11 Crikey also puts in a good showing.

The SMH’s spike on 6 March is largely due to a piece by economics editor Ross Gittins, who takes federal Labor to task over its criticism of the Coalition’s election promises (250 tweets). Two days later, The Conversation takes the lead, but without a major story of its own – several of its articles gain between 40 and 100 tweets that day. And in between, even the Brisbane Times’ usually sedate opinion section rises to temporary prominence, thanks to a strongly worded opinion piece from author John Birmingham which encourages Tony Abbott to rein in immigration spokesman Scott Morrison, if not quite in such civilised language (400 tweets).

Over the course of the following week, the Sydney Morning Herald records a strong result on 13 March, led again by Ross Gittins who warns us that “we worship materialism at our own peril” (130 tweets), while that same day it’s Crikey’s resident cartoonist First Dog on the Moon who raises that site’s profile with a cartoon that lampoons News Ltd.’s hysterical reaction to the proposed new media regulation regime (160 tweets). The Conversation’s strong performance two days later is once again due to a range of factors, on the other hand: star recruit Michelle Grattan’s article about the lessons Tony Abbott should learn from John Hewson’s defeat in the unloseable 1993 election gains her some 80 tweets, but several other stories also come close to that mark.

Given what we know has transpired in the meantime, however, do these two weeks simply constitute a period of treading water as Australia’s Twitterati waited for the supposedly inevitable Labor spill – or have they stopped caring altogether? Hopefully, the next ATNIX update will be able to provide an answer to those questions.

Shortly after the new Pope was announced, Zeynep Tufekci (@techsoc), a widely followed (12,961 followers at the time) social media researcher, announced that Jorge Mario Bergolio used the personal Twitter account @JMBergolio, the same false account mentioned in the article cited above.

Here is the original, mistaken tweet:

The account was outed as a fake within minutes by several of Tufekci’s followers. See some of the reactions here:

Tufekci, as well as the New York Times blog The Lede (@the lede), corrected the mistake by posting new tweets. Here Tufekci’s reaction to what happened:

One of Tufekci’s correctors raised the issue that good journalism needs to “verify the source” before it publishes (Michelangelo Nottolo, @fefanto), and this brings me to point number one I want to make about this incident: newsworthy occurrences heighten people’s demand for information. The media, and increasingly the citizen journalists among us, feel a demand and desire to be the first to provide this information and announce updates in situations that transcend routine reporting practices. Split-second decisions are made about what to publish and thorough research is sometimes neglected. Inaccurate information is brought into circulation. Now, this is not necessarily something new or peculiar to Twitter; when extraordinary things happen, people want up-to-date information about them as quickly as possible and journalists working with traditional news media have misquoted sources and misinformed the public in the past. Yet the likelihood of misinformation being communicated, and the speed at which this misinformation travels, are heightened with the immense number of people who use new media tools like Twitter. While social media are increasingly enrolled as useful tools for disaster management, false information can also go viral in times of heightened activity, as in this example from Hurricane Sandy.

However, an expanded community of users producing and consuming information, like that existing on the Twitterverse, also means that misinformation is more quickly detected and outed. This is my second point: on Twitter, expertise is easily asserted by the citizen journalist but also easily questioned by her followers.

‘I want a feature’

Finally, Tufekci’s mis-tweet raised a discussion about how to manage this kind of occurrence on Twitter, i.e. how best to correct a false tweet, beyond simply creating a new one with the correct information and an acknowledgment of the falsity of the previous one. Tufekci’s false tweet was retweeted 37 times (within 46 minutes), whereas the correction was only retweeted once (within 39 minutes). Tufekci did not want to ‘delete my tweet – as if to hide my error’. She bravely acknowledged that ‘honest mistakes happen’ and contemplated the best way of rectifying her error. She called for a feature on Twitter that provides a way of reaching those who are reading (and re-tweeting) the false tweet with updated information. The feature should mark the erroneous tweet as ‘retracted’ or ‘corrected’ to make visible to anyone who sees it that it provides false information and has been corrected. Furthermore, she proposed that the feature should reach out to all of those who retweeted the erroneous tweet and inform them of the correction. I would say, Tufekci is onto something… You can check out her own account of the occurrences on her blog.

Tufekci argues that ‘newspapers can append corrections to articles’. In this way, she likens Twitter to traditional media outlets and demands the same options for handling the communication of news. Yet a Twitter correct feature like that envisioned by Tufekci would actually extend the possibilities of correction that newspapers have currently.

When a newspaper publishes a correction to an article in a previous edition, it has no guarantee that those who took in the false information will also read the notice that alerts them to its incorrectness. A direct message, automatically distributed to all those who retweeted a false tweet, would ensure that at least these readers are informed of the mistake. Of course, that still leaves those who read but did not retweet the mistweet in the dark, as well as those who retweeted the retweet of the mistweet… I’ll stop there before it gets too complicated, but as I said, I think the @JMBergolio mishap on Tufekci’s Twitter and the feature she calls for certainly should be something Twitter developers should consider.