There are three major stories in this campaign:

1. Who will form government? The incumbent Conservative / Liberal Democrat coalition are fighting the election separately, and frequently in opposition to each other. Experts and polls suggest that a whole range of outcomes are possible, including both majority government for the Conservatives and Labour, however the smart money suggests either a minority government (7/4 Labour, 5/2 Conservatives) or a coalition. Amongst the coalition options, a renewal of the Conservative / Liberal Democrat coalition is possible (6/1), as is a partnership between the Liberal Democrats and Labour (13/2). The Scottish Nationals are another possible coalition partner for Labour (16/1 or 20/1 with the Lib Dems also included), while UKIP and the Democratic Unionists may still be needed to get either party over the line. Unusually for the UK then, we have a lot of electoral calculus in play.
2. How will Scotland vote? As above, the SNP may play a role in a coalition, but Scotland seems set to vote on very different grounds from the rest of the UK. A recent poll suggested that almost half of both Labour and Conservative voters would consider tactically voting for the other major (English) party, if it prevented the SNP being elected in their seat – something that would be unheard of in basically any other seat, in a hangover from the Scottish Referendum. That said, they are still expected to gain a large number of seats in Scotland, and thus put themselves in a position of power at Westminster.
3. Finally, there’s the UKIP factor. As the graphs below show, UKIP are one of the most talked-about parties of the campaign, well ahead of their expected representation in parliament (although, we should acknowledge, the UK has a first-past-the-post system, and UKIP’s representation would likely be higher in a proportional system). Paddy Power suggest that they will receive fewer than 3.5 seats (8/11), compared to 43.5 for SNP, yet the two seem to be roughly equivalent in terms of discussion on Twitter. Of course, pure volume of conversation doesn’t tell the full story, and much of the conversation around UKIP may be negative in nature – yet, our overall sentiment gauge shows little difference between UKIP and the other political parties in that regard. So, this will be interesting to watch — will interest in UKIP die down as their political prospects recede, or will we see a surprise on election day?

Aside from these, our live graphs of Twitter activity around the election tell a story of their own and are designed to be explored on a daily or even hourly basis as the social media conversation shifts in volume, tone and topic during the campaign. Previously, we have seen that major shifts in conversation do not just make for interesting journalism, but can also be cause of speculation about how the election might actually play out. We are expecting to see a more exciting representation of the conversation during this election, compared to our previous work in Queensland and new South Wales, due to the higher volume of election-related social media conversations across the UK.

The most notable change compared to our previous election coverage is the addition of the pie charts, which we think provide a much clearer visualisation of the share of conversation, and clearly compare the whole-of-campaign trends with developments over the past 24 hours. Also included are sentiment breakdowns per party, alongside currently trending hashtags, and an analysis of the total conversation volume over time.

Overall Conversation Share

Sentiment

Volume of Conversation

We plan to release some further graphs as the 7 May election date approaches – including a look at particular battleground seats, and a breakdown of the “positive” conversation around parties.

Hypometer is also undergoing some significant development in the lead-up to our first launch product – also to be released in May. You can follow the progress on the Hypometer project blog.

The New South Wales Election Social Index (NSWESI) tracks a combination of the key hashtags (#nswpol, #nswvotes, etc.), keywords relating to the parties and politicians, and tweets by and @mentions of candidates across all parties, to the extent that we have been able to identify their Twitter accounts. We’re combining the headline figures from our analysis of this dataset into three live graphs which are embedded below, and which are available for embedding on other sites. The graphs are updated with new data every five minutes.

In addition to the analytics for the various parties, and for the two major parties, this time around we are also adding some experimental sentiment analysis. As is by now well-established, sentiment analysis of individual messages – especially when they are as short as tweets – is very difficult, as standard sentiment solutions are struggling considerably with rhetorical devices like irony and sarcasm. However, in aggregate this analysis may still generate some useful overall patterns – but please take them with a grain of salt for now.

NSWESI: Overall patterns across the parties

NSWESI: Major party contest

NSWESI: Sentiment and trending topics

To embed these graphs on your own site, please use the following code:

<img src=”http://dev.thehypometer.com/images/election-allparty.png” style=”width:600px”> <img src=”http://dev.thehypometer.com/images/election-2party.png” style=”width:600px”> <img src=”http://dev.thehypometer.com/images/election-sentiment.png” style=”width:600px”>

Hypometer is a QUT-based commercial start-up which tracks and ranks social media activity around major topics, events and brands with assistance from qutbluebox, the University’s innovation and knowledge transfer company. For more information on The Hypometer, please contact Katie Prowd (k2.prowd@qut.edu.au). For more information about the principles behind Hypometer technology, see the Telemetrics Project.

As in previous elections, the core focus for our social media analytics activities remains on Twitter, though this time we’re also adding Instagram to the mix. For the purposes of our analysis, we are tracking a combination of the key hashtags (#qldpol, #qldvotes, etc.) and keywords relating to the major parties and their leaders, as well as tweets by and @mentions of all of the Twitter accounts associated with local candidates across all Queensland electorates.

But while in earlier elections we’ve posted weekly updates of the major social media trends, this time we’re moving to a real-time visualisation format. Working with the team behind last November’s G20 Hypometer, which was featured extensively on television and in online publications during the course of the event, we’ve now launched the Queensland Election Social Index (QESI):

The QESI Hypometer (click here for full size) combines the Twitter and Instagram data to show the focus of current social media discussions about the election, aggregated by party. Mentions of the major parties within popular hashtags such as #qldpol, #qldvotes and #qldvotes2015 are incorporated in real time, while mentions of the candidates of each political party are added on a slightly delayed basis. Percentage changes are shown on a day-by-day basis, while the volume graph is updated each hour.

A second QESI Hypometer focusses specifically on the two major parties, and also compares mentions of the party leaders, Campbell Newman and Anastacia Palaszczuk, also in real time. This Hypometer (full size here) shows the top trending hashtags within the election discussion.

To date, there has been a notable shift in conversation, from a strong focus on the LNP during the first week of the campaign (at times commanding  more than 70% of the total conversation) towards a greater level of debate about the ALP: towards the end of the second campaign week, the LNP is capturing a little over 54% of the total conversation since the election was declared. Together, Labor and the LNP clearly dominate the conversation, however, with the minor parties recording less than 5% between them. Campbell Newman also remains a far more frequent topic of discussion than Anastacia Palaszczuk, with a share of over 79% of the conversation. In total, at the time of writing the QESI Hypometer has tracked almost 85,000 posts across Twitter and Instagram since 6 January.

Refresh this page every hour or so to see the latest updates on how these numbers are developing. We’ll also post further analysis of key trends and developments over the remainder of the election campaign, and hope to deploy a similar election Hypometer again for the New South Wales election in a couple of months.

The two QESI Hypometers are also available for embedding:

<iframe style="overflow: hidden; height: 700px; width: 100%;" src="http://dev.thehypometer.com/election-allparty/embed" 
width="100%" height="1000px" frameborder="0" marginwidth="0" marginheight="0" border="0" scrolling="no"></iframe>

<iframe style="overflow: hidden; height: 700px; width: 100%;" src="http://dev.thehypometer.com/election-2party/embed" 
width="100%" height="1000px" frameborder="0" marginwidth="0" marginheight="0"></iframe>

Hypometer is a QUT-based commercial start-up which tracks and ranks social media activity around major topics, events and brands with assistance from qutbluebox, the University’s innovation and knowledge transfer company. For more information on The Hypometer, please contact Katie Prowd (k2.prowd@qut.edu.au). For more information about the principles behind Hypometer technology, see the Telemetrics Project.

Update (13 Nov): The interactive G20 maps are available at http://g20.thehypometer.com/maps/ and https://mappingg20.cartodb.com.

_______________________

In mid-November 2014, Brisbane will play host to the 2014 G20 Leaders’ Summit. Over the course of the summit, in its lead-up, and in its aftermath, the Social Media Research Group will be mapping the social media activity (Twitter and Instagram) that surrounds the event. In particular, we will be geo-mapping Brisbane-based, G20-related social media activity onto an interactive map of the city.

The summit, which takes place over the weekend of 15 and 16 November, will potentially be highly disruptive to those living and/or working within the declared and restricted areas that cover most of Brisbane’s CBD. Even leaving aside the possibility of Brisbane witnessing the kind of dramatic protest action that accompanied the 2009 and 2010 G20 Summits in London and Toronto, the Queensland Police Service has advised that Brisbane residents and travellers to Brisbane should, at the very least, expect disruption to public transport, roads, and parking in the CBD and South Bank area. In mapping the social media activity surrounding the G20, we aim to see how and, importantly, where discussions and debates about mobility, accessibility, safety, and security in and across the city are played out.

The Brisbane G20 social media map, which will go live on 13 November, will show public tweets and instagram photos related to the G20 and its dominant and emergent hashtags. The map will show geotweets (i.e., that very small percentage of tweets that contain embedded coordinates) as well as geotagged Instagram photos (which run at a much greater percentage of the whole, when compared with Twitter). Usernames will be removed, but the tweet contents and images will be able to be viewed on the map. We will also use a process known as geoparsing to identify latent locational information in the text of G20-related tweets and to assign coordinates to them if they match locations within the declared and restricted areas.

#colourmebrisbane: mapping the G20 Cultural Celebrations

We have tested this process in creating a social media map related to Colour Me Brisbane, one of the G20 Cultural Celebration events run in the lead-up to the Leaders’ Summit. Colour Me Brisbane, which ran every night from 24 October to 9 November, was a series of interactive light and projection installations set up at a number of iconic locations across the Brisbane CBD, including Parliament House, the convict-era Commissariat Store, City Hall, and the South Bank cultural precinct. Residents and tourists were encouraged to follow a Colour Me Brisbane trail around the city, which would take them to each location, and were encouraged to share their experience of the city via social media.

We tracked Twitter and Instagram activity tagged with the official #colourmebrisbane hashtag over the course of the Cultural Celebrations. From 23 October to 9 November, 324 tweets were tagged #colourmebrisbane. Of these, 32 (or 10%) were geotagged (i.e., had embedded coordinates). Geoparsing the remaining 292 tweets using a custom-built gazetteer of the G20 declared area returned a further 94 geo-locatable tweets, meaning that we ended up with 126 #colourmebrisbane tweets (or 39% of the total) that could be placed on a map of the Brisbane CBD. In comparison, the percentage of geotagged #colourmebrisbane Instagram photos was much higher. Of 1794 #colourmebrisbane tagged Instagram photos posted between 23 October and 9 November, 801 (or 45%) were geotagged. In total, we were able to map 44% of the total number of tweets and Instagram photos tagged with #colourmebrisbane. The resulting map shows the clustering of social media activity around particular Colour Me Brisbane sites, particularly South Bank and Queen’s Park/the Treasury Casino and Hotel on either side of the Brisbane River.

A note on viewing the map: The #colourmebrisbane map is an intensity map, meaning that the locations that appear the most (as geotags or place mentions) are darker coloured than those with fewer mentions or geotags. Where multiple tweets or Instagram images are layered on the same set of coordinates, only the most recent tweet or image assigned to a specific set of coordinates will be viewable as it will be sitting ‘on top’ of previous tweets and images assigned to those coordinates. In other words, the topmost tweet or image on a given set of coordinates will obscure earlier tweets and images assigned to the same coordinates; however, the intensity of the placemarker hue at those coordinates will indicate the density of tweets and images related to that location.

G20 Hypometer

As an extension to the G20 social media mapping project, we have developed a simple user interface to visualise the Twitter data collected and create a conversation around what it means to be the most talked about country at the event.

This interface, the G20 Hypometer, is a virtual live score card especially developed to measure Twitter conversation about the G20 Leader’s Summit and participating countries.

The technology is a simplified adaption of the original Hypometer, which was developed to measure ‘hype’ for upcoming shows on Australian television, and the Big Brother Hypometer, which measures pure volume of conversation around housemates.

In our first test of a non-television event for the Hypometer technology, we are tracking the real-time conversation around #G20 (and other unofficial hashtags being used) and the leaders and countries mentioned within that data to give us a running total of G20 interactions for each country. It will also be able to tell the user the daily numbers for each country, overall conversation around the official and unofficial hashtags, and identify emerging ‘trending’ topics during the event.

The AFL Grand Final on 28 September between Sydney and Hawthorn saw a total of 68,033 tweets matching pre-identified keywords between 2pm and 6pm, at a peak of 706  per minute, with spikes relating to a number of the games key events:

While only a small number of these (~2.5%) were geotagged, they given an idea of the worldwide spread, with clusters of users within the United States and the UK, as well as Australia:

However, we can do better than that for Australians. Using our database of Australian twitter users, which Axel Bruns has discussed previously, we are able to estimate the location of a far larger percentage of users:

As you can see, the vast majority of tweeters for the AFL Grand Final were located in Victoria, representing almost 44% ofo the total. This does not account for variance in state population, but is significant in comparison to the NRL tweeters. Speaking of the NFL, their Grand Final on 5 October saw 72,031 tweets between 6pm and 9pm (Brisbane time). On the chart below, we have plotted the score differential (as Rabbitohs – Bulldogs) against the social media activity, and the correlations between the periods of high activity and scoring moments is clear, as well as the increase in engagement while the score was tied between 7:50 and 7:55pm Brisbane time:

Here again, the international representation is shown on the world map, with a slightly higher representation in northern England (where Rugby League is traditionally played), and slightly less in the US, in comparison to the AFL:

The Australia-wide representation, based on our user database, is notably different for the NRL, with NSW and QLD overtaking Victoria in social media activity:

Overall then, a familiar story, and a distribution more or less as you would expect. Despite being longer, the AFL attracted less activity than the NRL, but a good portion of that difference could be attributed to the fact that the AFL GF was rarely close.

Given this popularity, and a significant overlap between the target market for Big Brother viewers and the social media platforms, it will be interesting to observe the extent to which social media activity (and perhaps, eventually, sentiment) acts as a predictor for votes on the show. In this blog, following the first round of nominations, first eviction and the first round of single nominations, we are going to look to the data from the last 2.5 weeks to try to test whether social media activity acts as a predictor of public votes.

So far, at least, it has been a mixed bag, but let’s start with the positive; the public vote for the ‘Perfect Pair’ dance competition, in which the winners were awarded $30,000, was held between the final two pairs – Lawson and Aisha & Dion and Jason. The public then voted for the pair with the best dance through JumpIn, but did they actually just vote for their favourite pair? If we use social media activity as a barometer, it seems that could be the case. Our data showed a tight race, which Lawson & Aisha just pipped, and indeed the public vote came back 51.8% in favour of Lawson & Aisha. Perhaps, if they had been up against, say, Travis and Cat – who were hardly mentioned this week – they would have won by even more:

Lawson also tells an interesting story in the overall polling; as seen in the chart below which highlights the running total for all housemates; largely anonymous until the dance-off and his decision to give Aisha the lions share of the prize money ($20,000) was rewarded in the social media volume.

Below is a running total of Twitter mentions for the pairs since launch night, however we will focus on the last week’s long-winded and highly debated eviction process for the time being. Nominees made up 5 of the six most talked about housemates on the night before the eviction process began, and the ones not being talked about were being carried by their partner based on the pairs table:

We can of course ask some other interesting questions from these charts: where were Skye and Lisa when they were ‘saved’? Were Jake and Gemma losers in the public vote due to anonymity, or hatred? What caused David and Sandra to be saved, when they were virtually anonymous through the first week, and only talked about subsequently in regard to David’s chauvinistic comments. Was it better for David to be hated, rather than not talked about at all? Related to this, there is the question of screen time and popularity inside the house, allowing us to address what went wrong for Gemma this week, given her achieved intent to secure airtime?

Up for eviction this week were Skye & Lisa, Jake & Gemma, Travis & Cat and David & Sandra. Ever since the Katie & Priya first week fiasco, Skye & Lisa have been by far the most talked about pair of the season and consequently were saved on Monday night as per our prediction based on the previous graph, with Skye & Lisa the most popular pair on the 22nd September. Interesting here, however, is that Gemma & Jake were the pair with the second most social media activity, and the most popular during the nomination period, indicating that the sentiment will also be a significant factor in creating further predictions.

While we have our own tool monitoring Big Brother discussion (http://bigbrother.thehypometer.com), Channel 9 (Mi9/JumpIn) have also launched a counter, the “Big Brother Radar”, which captures tweets and Facebook statuses by those who seek, deliberately, to be noticed by the radar using official C9 hashtags (e.g. #BBAUGemma). Our tool, by contrast, attempts to measure the underlying volume of discussion (and, by possible inference, interest) in the competitors as a whole, on social media.

Going forward, we hypothesise that those housemates who the public have no interest in will be those who struggle in a ‘vote to save’ format. That said, it’s probably not advisable to bet based on this information. It may be that the Radar format serves as a better prediction of those likely to be evicted (i.e. the effort to post with the correct hashtag is correlated to the effort to vote), it may be that sentiment proves highly significant, or indeed it may be that social media is not a good barometer of the BB voting public. Whichever of these proves to be the case however, the data is sure to be interesting.

Finally, it is worth noting that one of the problems of a lack of live feed – which we have ranted about previously – and indeed this year any live updates at all is that it allows producers to largely control the message; hence, social media reaction largely follows the amount of airtime given to contestants and the plot lines developed, much like a soap. By contrast in the USA, with 4 live camera views running 24 hours a day, users are able to create and share their own storylines about the housemates — generating ‘hype’ for the show which we do not see here. In Australian Big Brother we are told what to think, and we’ll leave it as an exercise for the reader how that reflects on wider society. Finally, we’ll leave you with a running total of the housemates mentions to date, where Skye continues to lead the way:

First, a look at the week that was.  Overall, the generic hashtags are being used consistently and in true Big Brother fashion, more hashtags are being used everyday, often introduced by CBS. Just this week I had to add, #BBTracker as well as a few running hashtags, #ZackAttack (a nickname for HG Zach), #Zankie (showmance between Zach and Frankie), #ZankieFallOut (the potential end of Zach and Frankie), and #EvictionPrediction. It’s a wonder why CBS continues to add hashtags that could possibly be steering people away from using their generic ones. What’s wrong with a simple #bb16?

Being elimination night, Thursday seems to be the peak show of the week with close to double the amount of tweets of the other two days. We will look at whether the ‘big night’ remains consistent in coming weeks in the interest of finding out whether context or type of show are more important for tweet numbers.

Total number of tweets containing the generic BB hashags for the week 6 – 12 July.

Taking a closer look at the Thursday show – conversation remained fairly consistent with no major spikes, just a lot of volume.

Total tweets by minute for the Thursday show.

HG Twitter Accounts

The graph below shows us which housemates’ twitters are getting the most mentions, and unsurprisingly at the top, is Joey, the first eliminated contestant voted out in a unanimous 13/13 vote. Two down the list is the most recently voted out contestant Paola, which we are guessing will probably be the most talked about by this time next week if there is a pattern. We saw this last year when HG Kaitlin was voted out early yet continued to be one of the most talked about HGs for the remainder of the series, largely thanks to her involvement in the racial-slur-scandal and somewhat thanks to her social media presence.

Number of times contestant Twitter accounts have been mentioned; 6 – 12 July.

Something new: Users by Timezone

Something we became interested in during last year’s BB broadcast was the difference in tweeters from one side of the US coast to the other, this year also considering the top 10 timezones joining the conversation with the generic hashtags:

Top 10 timezones using the generic BB hashtags on Twitter; 6 – 12 July.

Eastern time tweet by far the most of any of the timezones which fits with the documented distribution of the US population (47% live in Eastern Time). However, people in Mountain Time are tweeting more about Big Brother than expected with their distribution being only 5.4%, but publishing 9.45% of the total tweets regarding Big Brother. We’ve established that the Quito (Ecuador) timezone aligns with Chicago / Central time, so those users who say they’re in Quito, likely aren’t.

Until next time…

Let’s take a look back at some of the bigger stories of the World Cup from social media, as well as the prominence of the event in Europe.

One widely reported research result from the knockout stages of the World Cup was how Twitter users reacted to the penalty shootouts. Twitter’s own research department put out a graph of the Greece v Costa Rica match, which was widely picked up in the press.

In particular, Twitter noted that sometimes “silence tells the story”:

Parallels can be drawn here to other events. Particularly, we looked in the past at how different forms of television spark Twitter conversation, with reality television frequently seeing peaks in discussion during the show.

This contrasts with dramas such as Sherlock, which often see their peaks at the end, with a similar “anticipation” window during the show itself.

The US (and Australia) loves football

As we discussed previously, the World Cup has set viewing and streaming records in the United States.

It seems the presence of Americans in the Twitter conversation hasn’t been significantly hit by their team’s elimination. Germany v Brazil had the highest viewing figures of any World Cup semi-final in American television history, and was the highest ranked non-US game ever on ESPN/ESPN2.

A look at tweets on generic World Cup hashtags from July 10-14 show the US led the way in number of tweets. Brazil ranked second, with locals still interested through their team’s third-place playoff (and, of course, any tourists who had changed their timezone). London ranked third with finalists Argentina in fourth place:

In Australia, SBS also reported new streaming records for its World Cup coverage across mobile and online, with users showing a large preference for “live” coverage versus on-demand. SBS’ World Cup multi-stream service (below) won many plaudits, with the only negative being that sound issues persisted throughout the final.

Comic relief

As ever, beyond the discussion of the matches themselves, social media remains a hotbed for sarcasm and humour. FIFA president Sepp Blatter was a source of controversy throughout the tournament, and – sitting next to Vladamir Putin – remained a source of amusement (and marketing) in the final, as shown in this tweet by Betfair Australia:

Also prominent during the penalty shootout that decided the Netherlands v Argentina semi-final was a mistake from British commentator Peter Drury, who was featured on the television feed that went to range of countries including Australia.

Drury has never been one of the most popular commentators, and his mistake – being ready to proclaim the Netherlands victors in the semi-final – quickly spread around the internet. See the Drury penalty call below:

The view from Europe

We started this series of articles discussing the role of brands during the World Cup, and that was one of the themes in Europe as well. In many cities you were unable to move without noticing some form of localised World Cup branding, including the following example from Cyprus (which did not qualify).

Noticeable across Europe, though, were extensive World Cup decorations: from bars in basically every city, through to the large screens that inundated public squares, and – in the case of Amsterdam – a sea of orange which descended upon the city and sat above nearly every pathway in the Centrum.

And that’s the World Cup.

The authors do not work for, consult to, own shares in or receive funding from any company or organisation that would benefit from this article. They also have no relevant affiliations.

This article was originally published on The Conversation.
Read the original article.

Particularly interesting in the discussion of streaming figures is that such activity is able to be measured in “streaming minutes” or “data transferred” – much more specific metrics than traditional audience figures.

Accurate global TV ratings are still a way off, considering the official FIFA World Cup 2010 Audience Report came out almost a year after the tournament.

Twitter and ratings are undeniably connected, but the extent of the correlation often depends of the type of broadcast: whether it’s a live sporting event, soap opera finale or reality television show.

Indeed, a breakdown of the global tweets by timezone shows the dominance of US viewers in the Twitter conversation (including non-English hashtags):

Previous work by Nielsen has shown Sports, Reality TV and Comedy are genres where tweets have a causal relationship with viewer numbers, with Nielsen reporting that in 28% of sports programming measured, tweets had an impact on viewing numbers.

As we contended in last week’s article, it’s possible viewers tweet when bored, as well as when excited, during a game. But it is also possible that those not watching the game are also tweeting about it, so any correlation between ratings and tweets, for sporting events, needs a bit more research.

Match tweets

The US/World Cup love story continues in the graph below with the US vs Portugal match dominating match conversation for the week, and taking the lead in our “tweets by match” table.

ESPN also found that the:

USA vs Portugal contest on Sunday, June 22 is the most-viewed soccer match across all US television networks, averaging 18,220,000 viewers.

The top match in this graph has roughly a third more tweets than any match in the tournament so far, with top matches in previous weeks peaking at around 263,000.

It’s also possible from what we have discussed above that the Brazil vs Mexico match was bumped up by the large Mexican contingency located in the US timezones, as well as the enormous Brazil following on Twitter that we’ve seen in previous weeks.

The most talked-about event by far at the World Cup last week was the Luis Suarez bite.

The bite followed two other incidents of Suarez biting in the past, creating a storm of online conversation that can be seen in the visualisation of the most common words in tweets mentioning Suarez (note also the prominence of “Snickers”, a recurring example of brand impact on the World Cup):

The controversy around the bite mostly relates to whether Suarez intentionally bit the other player or just fell in an unfortunate position making it look like he bit him – as some Uruguayans have argued. Again, asking the question of whether video-technology should be more widely used in the game as recently discussed by Miguel Sicart.

Diego Maradona, the Argentinian whose hand-ball goal in the 1986 World Cup sparked much controversy said:

This is football, this is incidental contact […] They have no commonsense or a fan’s sensibility. Luisito, we are with you.

And a Reuters report notes:

The referee did not spot the incident during the match, but FIFA’s rules allow the use of video or “any other evidence” to punish players retrospectively.

Indeed FIFA did punish Suarez, announcing a nine-match ban on June 26 (the second spike visible in the graph below):

While the correlation is clear between real-time events and Twitter, the graph above quantifies just how vocal Twitter users have been around the Suarez incident, with the bite generating more than 3,500 tweets per minute at peak.

The lower volume for the announcement of the ban is also a signifier of the number of people watching the game(s) live and tweeting, versus those who use Twitter as a more general information source or discussion platform about the World Cup.

The authors do not work for, consult to, own shares in or receive funding from any company or organisation that would benefit from this article. They also have no relevant affiliations.

This article was originally published on The Conversation.
Read the original article.

Here, we look at the shift in conversation as the tournament begins to take shape – who is excited, bored or really winning on Twitter? – but first, a taste of what’s happening on social media in Brazil.

The opening ceremony and first match, Brazil vs Croatia, were huge successes on television and on social media. Brazilians, of course, probably talked about nothing else that day – but in Brazil, much of what was said was politicised.

FIFA was massively criticised for choosing a Belgian producer over Brazilians for the opening ceremony.

Francamente ! Na terra de Paulo Barros e Rosa Magalhães chamam um belga pra fazer uma bobagem de abertura destas!

— Leda Nagle (@Lnagle2) June 12, 2014

Translation: Honestly! In the land of Paulo Barros and Rosa Magalhães [two of the most successful Brazilian Carnival producers] they called a Belgian to do a silly opening like this!
– Leda Nagle, Brazilian journalist.

Another major disappointment was the disappearance on the official FIFA images of the moment that a paraplegic gave the initial kick-off using a mind-controlled exoskeleton built by the Brazilian scientist Miguel Nicolelis.

O genial exoesqueleto usado pelo rapaz que daria o primeiro chute infelizmente se perdeu na transmissão da abertura. Uma pena.

— Fernando Meirelles (@fmei7777) June 12, 2014

Translation: The exoskeleton worn by the guy that would do the kick-off unfortunately got lost in the opening broadcast. What a pity.
Source: Fernando Meirelles, Brazilian film-maker.

E teve exoesqueleto mesmo. Lamentável o desprezo total da transmissão ao que deveria ter o principal destaque. pic.twitter.com/PqDN9MUSEI

— Impedimento (@impedimento) June 12, 2014

Translation: And there was the exoskeleton indeed. Regrettable the complete disdain in the broadcast to something that should be in the spotlight.
Source: Impedimento, popular website dedicated to South American football and culture.

Still, others strongly criticised the crowd chants attacking the Brazilian president.

Parte do estádio grita: “Ê Dilma, vai tomar no c.. “. Outros gritam: “Ê Fifa, vai tomar no c…”

— Jamil Chade (@JamilChade) June 12, 2014

Translation: Part of the stadium shouts: hey, Dilma, f* off. Others shout: hey, Fifa, f* off.
Source: Jamil Chade, Brazilian journalist.

Updating the top matches

In our last article, we noted that Brazil vs Croatia was the most talked about match on its official hashtag (#BRAvsCRO), some distance ahead of England vs Italy, which was closely followed by Germany vs Portugal, Spain vs the Netherlands and Argentina vs Bosnia and Herzegovina. The updated chart, through the matches of June 21, looks as follows:

Of particular note here is that we have a new leader, in the Brazil vs Mexico match (an otherwise unspectacular 0-0 draw), with the Argentina vs Iran fixture (a 1-0 Argentina win, which Iran looked like winning at times) in second place.

The prominence of these two matches raises questions of whether people look to Twitter to fill in boring games, as well as to comment on exciting ones. The next three are familiar fixtures from the first week of matches.

Many of those at the bottom are the result of people using reversed hashtags in their tweets. Noticing this for the England vs Uruguay fixture, we also tracked the reverse hashtag specifically (#ENGvsURU), and recorded in excess of 27,000 tweets compared to 88,236 on the official hashtag (#URUvsENG).

So, while the official hashtags are performing as some form of marker, their success is not universal. One explanation for this is that while in Europe, the standard form is “Home Team vs Away Team”, for Americans the familiar format is “Away Team vs Home Team”, and so ordering hashtags for international audiences can be difficult.

What’s being shared?

Last time, we discussed how brands were dominating the conversation on official World Cup hashtags. This time, we’ll take a look at what is being shared on the match hashtags themselves.

As with last week’s data, we again see @worldsoccershop heavily represented, with their offer to give away free shirts if you retweet and a specific event happens (such as Ronaldo scoring in the Germany vs Portugal match) drawing a massive response.

Tellingly, the other tweets are largely dominated by US related content, the top two being ESPN responses (@Sportscenter being an ESPN-operated account) to the US’s victory over Ghana.

The first non-US tweet comes from the UK’s Sky Sports, and their @SkyFootball account, asking for responses on a penalty in the Brazil Game. Sky, interestingly, are not broadcasting the World Cup in the UK.

Other notables in the top 20 include celebrities such as Piers Morgan and Kobe Bryant, the US’s Comedy Channel (also not a World Cup broadcaster), asking Americans to “RT if you think WE WILL WIN”, and a quote from an unofficial Simpsons Quote Of The Day account, but really, @worldsoccershop was the huge winner.

The limitations of the 1%

As we discussed last time, the representativeness of Twitter research by those not subscribing to data providers such as GNIP is unclear with the World Cup, as Twitter traffic continually exceeds 1% of the total amount of tweets published at any particular time.

The flip-side of that limitation is we are able to graph the times at which conversation around the World Cup; through the team accounts, tournament hashtags, match hashtags and television hashtags we are tracking, exceeds that 1%, and by how far.

Of course, at any particular time, there are also many tweets relating to the World Cup which do not contain any of the previously mentioned identifiers:

The blue indicators in the graph above are the number of total tweets per second that exceeded 1% of total Twitter traffic.

Notable is that the World Cup is generating a smaller portion of the total Twitter traffic as it continues – which may not be much of a surprise – but also that while the opener generated the most prolonged period of >1% traffic, the matches on the morning of June 14 AEST (the matches of June 13 in Brazil) were the most prolific of the tournament on a per-second basis, with a particular peak during Spain’s demolition by the Netherlands.

It has yet to be seen how the next phase of the tournament will play out, and least of all what role Twitter will play; whether as a tool for excitement or boredom.

The authors do not work for, consult to, own shares in or receive funding from any company or organisation that would benefit from this article. They also have no relevant affiliations.

This article was originally published on The Conversation.
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