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…

A week prior to the premiere, we set up a Twitter collection machine to track off all of the current @mentions and hashtags for BB16, adding more as they were created as well as the contestant names and Twitter accounts.

Generic hashtags at this stage include: @CBSBigBrother, @BBHOH, BB16, bblf, bbmvp, BBkickoff, BBAllNighter, BigBrother, BigBrother16, bbhoh, BBselfie, BBAD, #HOH:

The graph above is a breakdown of tweets containing the generic hastags per minute over 12 hours around the Big Brother premiere night one of two.

Tweets peaked at just under 80k for the hour, with the first spike being a mass retweet of pop star and contestant’s sister, Ariana Grande:

everybody watch big brother tonight at 8pm @frankiejgrande we love u so much #bb16 #teamfrankie

— Ariana Grande (@ArianaGrande) June 25, 2014

 

The second (expected) peak occurred at 8:01pm, as the show began, and the largest peak was due to the hugely built up ‘twist’ reveal and another mass retweet of Ariana Grande:   Ariana Grande RT #2

we’re. shaking. watching this challenge #bb16 “how’s my hair look” @frankiejgrande crying i miss u #bbfrankie — Ariana Grande (@ArianaGrande) June 26, 2014

Controversy, again

Houseguests were revealed only a few days prior to the premiere, probably to spark conversation as well as bump up live feed subscriptions at the last minute. As we discussed around this time last year, controversy is usually no mistake in the reality context, particularly for shows like Big Brother that rely on it. The early release of HG names sparked instant controversy with the network already being under scrutiny for choosing Frankie Grande, who already has a lot of public exposure as a YouTube personality and brother of Ariana Grande. The graph above clearly argues that controversy is the best way to cause online discussion, with both peaks being due to the casting of Frankie.

CBS has also made another bold decision in revisiting the race scandal of last year by introducing another controversial cast member who has already gained a lot of support, and hate, on Twitter:

Indeed, we can track the success of CBS’s efforts in creating controversy by looking at contestant mentions across the two nights:

As predicted, Frankie Grande was the most talked about HG thanks to both the controversy of his casting and the mass retweeting caused by his sister’s Twitter following. Because contestants were released into the house over two nights, a breakdown of each night is below:

In this graph, the Twitter conversation about “Frankie” almost mimics the overall Twitter conversation in the earlier graph indicating he was not only the most talked about HG but also the most talked about thing overall.

On the second night, tweet numbers mentioning contestants was comparatively a lot lower than the first night, with Caleb being featured in a maximum of 462 tweets, and Zach, 459 tweets. Other contestants were also more likely to get mentioned, although Frankie (purple line) remains relatively high despite being introduced the night before.

Sentiment in tweets

Another interesting thing I’ve noticed is the increase in what I’ll call ‘positive intention’ tweets from last year to this year. People seem to be actively suggesting that fans  be nicer to one another and the contestants this year, using the words  ‘support’, ‘love’ and even a hashtag; ‘#beNICE’. While the sentiment is evident across Twitter and Big Brother blogs now, it will be interesting to see how #beNICE fares a week or two into the show when people start to take sides.

That being said, CBS Network and BB fans have already created a number of new or, ‘running’ hashtags for fans to use to takes sides like #BBFrankie and #TeamFrankie, as well as what will likely be temporary hashtags to talk about current alliances in the house like #TeamAmerica (which we’re not tracking as it’s widely used elsewhere) and #TheCrazy8s.

Essentially, an infographic combines key text, imagery and design to tell a story. It is visual shorthand with the ability to communicate in-depth information. Infographics allow information to be viewed and understood by a wide audience, not just by academics. The most crucial and interesting information is singled out from a pool of data, making it more relatable and compelling to the general public.

When it comes to mapping the Twittersphere, the amount of information is overwhelming. Infographics will play a crucial role in the success of this project within the media and general public. The main goal of the infographics I have created is to compare the US and Australian data, highlighting the difference in relationships between Twitter and reality television. My approach to designing infographics for this project has revolved around picking the most crucial data and displaying it in a simplified and uniform manner. The font and colour choice creates a contemporary aesthetic that appeals to a wide audience. Currently, the end goal for this series of infographics is to create a completed publication for both print and online viewing.

My approach to the design process of an infographic

Design Iteration 1

The most important step is to select the story you want the infographic to tell. For this particular infographic, I wanted to compare the number of viewers to the number of tweets to show that there is a dramatic difference between US and AU tweet habits in regards to reality television. The first obstacle is the raw data as it compares oranges to apples. It has to be transformed to be comparable and relevant to one another. The conversion of reams of data into a single number needs to be systematic and fair to be a true representation.

I originally wanted to show the number of tweeters to the number of viewers as a percentage, however the numbers just weren’t there. Percentages below 1 aren’t powerful, so a ratio was used in their place. The final infographic read 1 viewer tweets for every 57 who watch The X Factor (US). The viewer numbers are averaged from the season, excluding the premiere and finale episodes. The premiere and finale episodes had to be excluded as they were skewing the averages for both the viewers and tweets.

Initially the tweet numbers used in design iteration 1 were all-inclusive, altering the story of the infographic. The gap between the US and AU tweet habits had been marginalised and subsequently the point was lost. In design iteration 2 the tweet numbers were substituted with unique authors, realigning the infographic with the initial story. Once the data is communicating the correct story, the primary aim is to assist the communication by presenting it as clearly and engagingly as possible.

In my first semester of university I was introduced to a term called ‘Chartjunk.’ It refers to the presence of any element that is not essential to the overall design. Anything that does not have a purpose or assist in the communication of the message needs to be removed. Design iteration 3 is all about refining and the eradication of said Chartjunk. The information is complex and it takes time to digest, so the design must be as streamlined as visually possible.

Design Iteration 2

Design Iteration 3

From Design iteration 2 to Design iteration 3 these are the significant changes that occurred:

• The amount of white space was increased so the eye is able to separate the information more easily and create a pathway for viewing.
• The number of font sizes was reduced and spacing between was altered to distinguish the headings from the body and in turn communicating more clearly.
• The individual numbers from each bar were removed and replaced by a simplistic scale. By adding a scale the viewer instinctively processes the information visually without the need of text.
• The blue column not only guides the eye through the infographic, but it also clearly shows that there is a relationship between the numbers contained within it. The key became obsolete with the addition of the blue column and was removed.

The design for this research project needs to be intelligent, simple and appealing. Through the iterative design process, the final solution for this infographic is the most powerful and successfully meets the design needs for this project. The infographics as part of this research project are an invaluable method of communication. With new data being added everyday to the growing Twittersphere, these infographics are just the beginning. I look forward to sharing the series of infographics I’ve been busy working on with you in the near future.

X-Factor was the clear winner of the Saturday night battle, doubling up Big Brother which was at a season low for average tweets per minute.  Masterchef however rated terribly on Twitter:

If, however, we give Big Brother the benefit of the doubt, and take a more typical show (in this case Thursday 2 August) rather than the Showdown format, it looks more competitive, able to keep pace with X-Factor and generating more tweets through airing over a longer period, with Masterchef still lagging well behind the other two, as the following graph (which timeshifts all shows to an identical ending point) demonstrates:

Finally, all three shows aired over a two hour period on Monday night, with a similar story to the time-shifted graph above:

There are a few interesting things here: the poor showing of Masterchef, the high peak of Big Brother in comparison to the other shows, but also the increase in Big Brother tweet volume as X-Factor concluded, which suggests a significant social media overlap between the two shows.

Big Brother Australia Update

Episode 4 of Big Brother Australia (Thursday night) followed much the same pattern as Wednesday’s discussed previously, with approximately 7,200 tweets over the hour of the broadcast, peaking at 164/min. It is worth noting that the array of different Australian timezones do have an impact on these totals, and because of the overlaps it is difficult to separate them as I have with the US broadcasts. However, as discussed last time the peaks do correspond to the Eastern Time zone viewing, which is what I will concentrate on here.

That said, here is the graph for Episode 4 from Thursday night:

In Australia this season, Friday Night football means a reduced 30 minute show on Friday. with the show also suffering from a major drop in ratings. While  Monday’s premiere reached 1.31 million and subsequent daily shows hovered around 1 million (1.04, 1.03 and 0.98), Friday’s show only reached 0.73m viewers.

Here is what it looked like on Twitter, with only 1326 tweets over the 30 minute broadcast (+ 5 minutes either side), peaking at 70/minute:

Saturday saw the launch of ‘Big Brother Showdown’, a re-imagined version of ‘Friday Night Live’, which seemingly did not resonate with viewers, with a new series low of 0.68million viewers. The twitter performance was similarly down, with 1,797 tweets over the 1 hour broadcast (+ 5 mins either side), and a peak of 76/minute:

Significance of a Live Feed:

While there are many differences between Big Brother in its various international incarnations, one of the most significant from a viewer engagement perspective (at the very least, this viewer) is the lack of a Live Feed during the return of both the UK (after the move from Channel 4 to Five) and Australian (Ten Network to Nine) series. Fans of the show have long made the argument that this impacts detrimentally on viewer engagement, while producers have argued that such a service is not cost effective in Australia, and that may well be true, however large numbers of viewers continue to complain each year.

Given the US (which maintains a live feed, on a subscription basis) and Australian series are currently running concurrently, I thought it might be interesting to look at the engagement / discussion on Twitter of both shows before and after  their broadcast slots. Even allowing for population / Twitter population differences (The US series is watched by almost 6x as many people, and has in-show peaks of around 2-4x the Australian broadcasts), the effect is obvious. While the Australian broadcast is lucky to receive 100 tweets/hr during the afternoon before a show, the US is hovering at 1000-2000, putting news from the show in front of a much wider Twitter audience.

The graph below takes advantage of a new TimeShift formula (utilized above to compare Australian Reality TV shows) to match Australia to US Eastern Time. I’ve also cut off the top of the Big Brother show from Thursday and Sunday nights (US Time) , which peaked at 65,000/hr and 25,000/hr respectively, in order to increase visibility at the lower end of the graph. As you can see, discussion of the US Live Feed on Twitter was greater than discussion of Saturday Night’s television show in Australia, and the two were fairly close for Friday night also:

When considering the viability of Live Feeds, such a social media presence cannot be ignored, and I continue to suggest that live feeds for reality TV shows are a weapon producers should use to their (social media) advantage.

Controversy provokes Tweets more than regular ‘game-show’ mechanics

Big Brother 15 has, since the first few shows, been beset by racism, sexism and other scandals, which they finally decided to air publicly on the 7 July CBS Broadcast, as I discuss here. The segment of the show in which the comments were aired heavily outranked the remainder of the episode in terms of tweets (peaks of 340/min vs. 100/min for other segments), and even attracted a West Coast audience (with peaks of 140/min), which as I will shortly discuss, is not a regular occurrence. This suggests that perhaps a wider audience was attracted to the show because of the airing of these segments, and the ratings for the show since the 7 July broadcast suggest that some of that audience stuck around – perhaps any publicity is good publicity.

[Note: This graph is not directly comparable to the ones that follow, as it used a previous version of our Twitter capture process]

The word map for this episode also clearly shows the dominant themes, with the main protagonist (Aaryn) and Racism both featuring heavily.

But, generally West Coast Audiences don’t tweet about tape delayed shows

Across all of the episodes, except the one portraying the racism scandal discussed above, a constant theme has been the lack of attention given to the West coast tape delayed broadcast of Big Brother. While the airing does show a noticeable spike in the traffic, this is from about 50 tweets per minute when the show is not airing (which is primarily discussion around the 24/7 live feed) to 100/minute, with peaks at 1/3 or 1/6 of East Coast levels, which is far greater than population alone would suggest:

10 July (More detail):

21 July (More detail):

There are a couple of possible theories for this; one is that many of those who care enough to tweet about the show care enough to find an East coast stream, and that this may be true more broadly, so that for sitcoms and other shows those wanting to join a conversation about an episode watch online, just as viewers overseas might. Another theory is that those tweeting about the show overlap heavily with those tweeting about the live feed, and as such many West Coasters would rather watch the live feed than the broadcast show; in which case this may be a phenomenon unique to Big Brother (and/or other reality shows with a live feed); I don’t have the data to draw a firm conclusion on that yet.

They care about tape delayed live shows even less

if you thought those graphs looked bad for viewer engagement from the perspective of West Coast broadcasters (and advertisers!), the live show figures are even worse. Each Thursday, the Big Brother eviction show is aired live on the East Coast, and tape delayed on the West Coast. While a power cut cost us the data from 11 July, Jeremy’s eviction on the 18 July was captured, and saw the West Coast airing of the show struggle to achieve 10% of the tweet volume of the East Coast broadcast (and the West Coast broadcast figures include people discussing the live feed, which is blacked out during the East Coast broadcast):

Guilt by (Twitter) Association carries into the media sphere

Separate from the raw analytics relating to each episode, I have also begun taking a look at the content of the tweets, in an aggregated form. Utilizing some methodology that my CCI colleague Axel Bruns has outlined, I took a look at tweets surrounding three houseguests who formed an early alliance called the “Triangle of Trust”, including Aaryn who was associated with the racism scandal discussed above. A theme of the Tweets (which I won’t quote specifically to avoid personal identification) and press reaction (See, for example, CNN/Jeremy, Daily Mail/Kaitlin) to-date is ‘guilt by association’, by which I refer to the degree that other housemates, particularly Jeremy and Kaitlin (who formed the ‘Triangle of trust” with Aaryn) have found themselves associated with remarks they didn’t make. A fuller description of what I did is in the longer post at my blog, but in summary a dendogram of terms and their proximity showed the association between different terms:

The same data can also be visualized as a 2D map of the terms, in which the closer they are, the greater the association:

And finally, the following chart shows how the terms associated with the three houseguests were distributed across the alliance members:

Big Brother 15 has proved an interesting test-case and proof-of-concept for me, in terms of both the current version of our Twitter capture software and also some additional analysis tools. I’ll continue to update on my own blog, and report back here when there are some significant findings.