How can we analyse tweets in a foreign language?

Recent analysis using the Brand Aura: discover tool undertaken during the French elections resulted in analysis published online.  This looked at what the French populace were thinking and discussing during the live TV debate through twitter as well as in the run up to the election day and also the reaction to Hollande being elected as President of France.

An example of the type of analysis that was published can be seen in the figure below.  This shows the main topics under discussion during the live TV debate and is hard for us to understand as it is (understandably) all in French.

The main topics under discussion by the French during the live TV debate

However it is possible for us to investigate the analysis shown here, and understand this in English (or another language if that suits us better).

Let’s start with the word in the top left of the centre circle: emploi.  We can look at the words in context of this word by clicking here (will open in a new window).

This analysis is still all in French which isn’t much good to us unless we can already understand French.  However, if you scroll to the bottom of the page, you should see a combo box with the words ‘Select Language’.  If you choose English as your preferred language (at the top of the list), then the word cloud will automatically be translated into English.

We can now see that the word emploi means employment.  We can also see that some of the words that are shown in the above figure have been translated for us: for example minable means pathetic and is in very close context to the main word of employment.  Evidently there is a big problem with employment in France.

Note that not all the words shown in the figure are in the word cloud shown here since the figure above collates words from the whole of the TV debate whereas this word cloud analysis is looking at a specific time frame of 30 minutes of data only.

We can investigate some of the other words in the same way.

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French elections

The Brand Aura: discover tool has been used to give an insight into the recent French elections.

Tweets were downloaded during the live TV debate between the two Presidential hopefuls, and also subsequently to look at how voters reacted to the election of Hollande.  It is worth noting that the tweets are almost all in French, since it is the French populace who are discussing this event.  The subsequent analysis is also in French, but using the Brand Aura: discover tool it is possible to analyse this in English.

To view the original analysis (in French) simply click on the relevant links: to see the analysis of the TV debate, click here; to see the reaction of the populace to the election of Hollande to President, click here.

The power of the Brand Aura: discover tool can truly be seen when we try to gain an understanding in English of what was said.  It is possible (and very simple) to do this using the Brand Aura: discover tool – for example, to view analysis from the night of the TV debate click here (will open in new window).

Initially this analysis will be shown in French, with the word ‘immigration’ in the centre of the contextual analysis and words surrounding it in context, with the closer the word is to the centre, then the closer the word is in context in our analysis.

If you scroll to the bottom of the page, you will see a drop down box which will allow you to select ‘English’ as the language to translate to.  This will translate the French words into English so that you are able to examine the issues that came up in discussion with ‘immigration’ during this period of the evening during the live TV debate (the analysis covers 30 minutes of the period only, as this is approximately how long each topic was discussed for).

Other words can also be searched for by using the box near the top of the page.

This once again shows the power of the contextual analysis approach – it is possible to undertake analysis in languages other than your own, without affecting your ability to draw insights into what is being said on your topic.

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Focus on McDonalds, Coca Cola, Intel and Nike: what cyber chat can tell us about a global brand

McDonalds and Coca Cola are in that select group as being two of the world’s leading brands.  The BrandZ Top 100 Most Valuable Global Brands 2011 puts McDonalds as the 4th leading global brand and Coca Cola as the 6th this year in terms of current and potential earnings on brand alone.

What does the Brand Aura: discover tool tell us about the context in which these strong global brands are talked about in everyday conversation?  Looking at Twitter data from 2nd – 7th Sep 2011, we can see firstly that the brand names, in this case ‘McDonalds’ and ‘Coke’ are used regularly in ordinary Twitter conversation.  As would be suspected, this shows they have become part of the everyday vernacular across the world.  Looking at the data in more detail we can see that Coke and McDonalds are both regularly found in context  with a verb –  ‘drink’, ‘get’, ‘have’.  People don’t just have a drink, they have Coke to drink.  You don’t just get a burger, you get a McDonalds.

Other words regularly associated with Coke and McDonalds are social, positive words such as ‘like’, ‘you’ and ‘lol’ (laugh out loud).  Using the brands Coke and McDonalds in cyber conversation with others makes a connection, something that everyone can understand therefore enhancing the online relationship.

Interestingly, what doesn’t come up regularly with either Coke or McDonalds are any negative sounding words.  The Coca Cola and McDonalds brands are strong with a positive aura around them when they are used in everyday conversation on Twitter.  There is little sign of the healthy eating message bringing down their brand in this context.

Nike and Intel are placed 57th and 58th in the same survey.  Although they are both a leading global brand, they are markedly down the list from the likes of McDonalds and Coca Cola.   So, can the Brand Aura: discover tool highlight a noticeable difference in the way these brands are talked about?

The first thing that we notice is the lack of verbs around the both Nike and Intel.  When we look at the words that appear regularly in context with the words Nike and Intel across Twitter data from the 2nd – 7th September 2011 we see a complete lack of verbs.  Clearly, they are different types of product to the likes of McDonalds and Coca Cola, but all the same we can say there is no sign that either company has entered the minds of consumers in the same way as the top brands.

The words that appear in close context to Intel on a regular basis are related to the function of its core product.  Words like ‘cpu’, ‘processor’ and ‘ram’.  These are factual words, with no emotions attached purely describing what it is.  Other words that appear in close context with Intel are ‘notebook’ and ‘laptop’.  When grouped together, it appears that Twitter users regularly use Intel when describing a product, for example I have a netbook with an Intel processor and XX Ram.  What this does show is that Intel processors are well thought of, enough to be mentioned by name.  But what Intel is lacking is the brand good will.  Unlike Coca and McDonalds, where we saw ‘like’ mentioned, there are no positive words used in association with Intel – other than purely technical terms, which require an understanding of what they mean for it to be considered positive or negative.

Nike, on the other hand, can be said to have this notion of brand good will.  The word ‘like’ regularly comes up in context with ‘nike’ in the Brand Aura: discover analysis.  Twitter users regularly use the specific names of the Nike products in context with the Nike name.  Words like ‘air’, ‘pace’ are regularly seen (Nike Air are a trainer product, Nike Pace are a football boot).  The other words used in context with Nike are ‘boots’, ‘socks’, ‘shoes’ and ‘you’.  Again this puts the product and the brand together – Nike boots, Nike shoes, Nike socks.  Twitter users are using the brand name together with the apparel to enhance their status and show their preference.  As you would expect from a clothing and footwear brand, the image is important, what other think is key shown by the use of the word ‘you’.

Overall, the one similarity across all four brands is the status that the brand gives the Twitter user.  Across the differing industries of beverage, fast food, clothing and technology the consumer uses the positive power of the brand to connect with others.  The Brand Aura analysis shows the ability of the brand to enhance the product itself – it’s an Intel processor and Nike shoes.  The most successful brands have achieved this to such a degree that the need for the noun disappears altogether – McDonalds & Coke exemplify this idea.

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Celebrity Big Brother – the participants

Brand Aura: discover has analysed the Twitter data between 8pm and 10pm on the night of the launch of Celebrity Big Brother.  We will go through each contestant in turn to give an early indication of which contestants are set to do well as the series continues.

Firstly, before looking at each contestants first name in the Brand Aura: discover tool, we can make some general observations from non-person specific key words.  When looking at the word ‘loving’, ‘Amy’ and ‘mskkatona’ appear in close proximity in the word cloud analysis, suggesting Amy Childs and Kerry Katona are early favourites.  Keywords ‘celebbb’ and ‘bbuk’ bring forth references to ‘Kerry’, ‘Amy’ and ‘Paddy’ illustrating the strong connection between these contestants and the viewers.

However, the references to Kerry in particular are not entirely favourable.  The search term ‘celebbb’ as well as showing ‘Kerry’ in close context also shows the words ‘could’, ‘send’ and ‘edge’.  The meaning from this is clear – having experienced well publicised breakdowns in the past, viewers are concerned for Kerry’s mental well-being in the house.  While not being complimentary of Kerry’s mental strength, it could prove a ratings draw for the programme itself, as Vanessa Feltz’s behaviour did for a previous series of Celebrity Big Brother.  Kerry clearly divides the Twitter audience, with her name found in high proximity to the word ‘worst’ in the Brand Aura: discover analysis.  Kerry is not the only contestant to appear in close proximity to the word ‘worst’;  ‘childs’ also appears, suggesting contradictory views of Amy Childs also.

We will now concentrate on the Brand Aura: discover analysis of each contestant in turn.  When we use ‘Kerry’ as a keyword, the duality of opinion mentioned above is clear.  On the one hand, we see positive words such as ‘love’ and ‘nice’.  On the negative, terms such as ‘snide’, ‘nasty’ and ‘tired’ appear in close proximity to the search word ‘Kerry’ in the Brand Aura: discover analysis.  Kerry’s previous history is also alluded to with words such as ‘crack’ and ‘snorts’.  As a contestant, Kerry Katona is one the Twitter users love or loath, but also one that people love to talk about.

Turning to the Brand Aura: discover analysis of Amy Childs, using the keyword ‘Amy’, we discover a pretty positive hue.  Critically, the word ‘win’ appears in close proximity, which singles Amy out as an early front runner to win Big Brother.  Other complimentary terms such as ‘great’, ‘love’, ‘funny’ and ‘loving’ also are closely related to ‘Amy’ in the word cloud, reinforcing the positive impression.  The twitter analysis shows that people have a generous attitude towards Amy with the words ‘good’ and ‘luck’ showing in our analysis.  Only time will tell if Amy Childs can keep this sentiment going while she is in the house, clearly that depends on the viewer’s opinion of her behaviour going forward.

Two other contestants are mentioned in context with the word ‘win’ in the Brand Aura: discover analysis, those being Jedward and Paddy Doherty.  As we have seen above, Paddy has appeared in context with ‘bbuk’, showing a strong level of interest in his appearance on the show.  When we look at the word ‘Paddy’, the word ‘win’ appears in close proximity in the word cloud, as well as the accompanying words ‘bet’ and gonna’.  Clearly, the Twitter users have put Paddy Doherty as a strong favourite to win.  As mentioned previously Jedward also appear in context with the word ‘win’.  When we examine the Brand Aura: discover results for the term ‘Jedward’ the opinion is decidedly more mixed with words like ‘fuck’, ‘off’ and ‘out’, ‘now’ appearing alongside ‘win’ and ‘love’.  Jedward are, like Kerry, a Marmite-like contestant.

Darryn Lyons comes through in the Brand Aura: discover analysis as the character Twitter users are most cynical of. Words closely associated with ‘Darryn’ include from ‘least’, ‘ego’, ‘exposure’, ‘enough’, ‘money’.  The Brand Aura: discover analysis shows Twitter users speculating on the reasons Darryn has entered the house, and showing their cynical side by closely associating Darryn with money, exposure and ego.  None of this is surprising considering his occupation outside the BB house, however it shows that Darryn will have to work hard inside the house to gain a level of popularity in order to get viewers to vote for him.

The Brand Aura analysis of Bobby Sabel and Lucien Laviscount are broadly similar to each other.  Words like ‘ohhhh’, ‘excited’, ‘marry’ appear in close proximity to both contestants, with Lucien receiving slightly more complimentary words including ‘brill’, ‘follow’ and ‘xxxxx’.  Both contestants are admired for their physical appeal, however this is a short term effect and may not translate into long term votes from the viewers.  It definitely gives both Bobby and Lucien an advantage on entering the house though!

There is little real interest in Pamela Bach-Hasselhoff as a contestant, with most of the discussion being around ascertaining who she is.  Words like ‘Baywatch’, Pamela’, ‘Anderson’ are examples of that appear in close connection with ‘Pamela’.  The same could also be said of fellow contestant Sally Bercow.  Words appearing in context with ‘Sally’ include ‘husband’, ‘speaker’ and ‘commons’ as her identity is confirmed.  Also appearing in close connection to ‘Sally’ are words like ‘global’, ‘recession’, ‘economic’, ‘meltdown’ and ‘fears’.  Sally Bercow’s close connection with the government, and the economic situation (although she is a member of the Labour party) could see her resented for making money out of her celebrity status.

Lastly,Tara Reid. The Brand Aura: discover analysis shows the words ‘kerry’ and ‘amy’ in very close proximity to ‘tara’ in the word cloud.  Tara is being compared with Kerry and Amy, whom, as we have seen above have very definite opinions formed out them.  In contrast, the word cloud for ‘Tara’ is fairly uninteresting, the only word that sticks out being ‘euughhh’.  Tara Reid will have to establish herself as a personality early on in the Big Brother house to gain some followers quickly.

This analysis was based on data gathered from Twitter on the launch of Celebrity Big Brother, and as such, shows the intial impression of each contestant as they enter the Big Brother house.  How this changes over the course of the show is yet to be seen, but the Brand Aura: discover analysis outlines the base from which they start.  As you can see, people’s initial impressions of them mean they are not all on an equal footing….

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Big Brother: first night on a new channel – is the brand still live and kicking?


The Big Brother launch was on air from 9pm on Channel Five.  Until then, the lineup had been gossiped about but not confirmed.  Therefore, this article is looking specifically at the Twitter data between 8pm – 10pm on the night of the launch when the show was on air and viewers had confirmation of the participants in the show.

Firstly, the Brand Aura: discover anlysis shows that Big Brother fans are still out there.  Looking at the word ‘loving’ we can see it linked with ‘bbuk’, ‘celebbb’.  Words like ‘funny’, ‘loved’, and ‘hooked’ were also closely correlated with ‘loving’ showing an high level of enthusiasm for the programme.  Fans were excited at the launch, and positive that they were getting a chance to see it after it was cancelled by Channel Four – the word ‘seeing’ and ‘again’ were closely associated with ‘loving’.

The words ‘Celebbb’ and ‘bbuk’ brought forth a few positive words such as ‘right’ and ‘works’ but were not strongly positive.  This ambivalence is more strongly seen when we look at the word ‘watch’.  Strongly negative words such as ‘never’ and ‘why’, ‘would’, ‘anyone’ are strongly associated with the word ‘watch’.  From the twitter data, the Brand Aura: discover analysis shows a negative sentiment coming through.  This can be clearly seen by looking at the words ‘worst’ and ‘crap’ as keywords.  Words closely associated with the search term ‘worst’ are ‘lineup’, ‘ever’, ‘watched’, ‘nightmare’ and ‘contestants’.  Starting out with a negative word like ‘worst’ would logically lead to negative keywords, but even having said that, this is a strong reaction from Twitter.  This is continued when we turn to the word ‘crap’.  Words like ‘slow’, ‘everything’, ‘lineup’ and ‘telly’ shows it is not a single or particular contestant that is being singled out but the show itself.

From the Brand Aura: discover analysis, we can say then that a strong level of enthusiasm for the brand has been severely mitigated by the negative reaction to the show itself and the lineup.   However, this is tempered by the fact that Twitter users are not necessarily viewers of the show, and so can exaggerate the negative sentiments beyond what is reasonably associated with the viewers of the show itself.  These factors taken together with the Brand Aura: discover analysis point to a polarised outlook of the programme, with highly positive on one hand and highly negative on the other.  And isn’t this clash of opinions what Big Brother is all about?

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Celebrity Big Brother – analysis from opening night

We have been asked to do some analysis on Celebrity Big Brother, and so we have looked to focus first of all on the opening night.  As usual, we have focused on data from twitter, and downloaded anything relating to Celebrity Big Brother.

To start with, let’s look at which of the contestants comes up in context with words like ‘best’, ‘favourite’,’great’,’funny’ or ‘cool’.  This is shown in the figure below, which shows how each contestant fared during the day and evening of the show.  Scores are shown for all tweets up to 6pm, between the hours of 6pm and 8pm, between 8pm and 10pm, and finally from 10pm until midnight.

This analysis shows that Amy Childs has a clear peak as the favourite contestant from first impressions.  Sally Bercow comes in second, and Jedward come in third.  It is noticeable that Tara Reid does not score at all – so no mentions of Tara in context with ‘favourable’ words.

By contrast, let’s look at who comes up on context against words suggesting negative sentiment, such as ‘annoying’, ‘idiot’, ‘stupid’, and ‘hate’.

This is shown in the figure below, and this time we see a different picture emerging.  Here due to a lower number of tweets the analysis simply shows the total score over the entire evening.

This time we can see that Bobby Sabel is clearly attracting alot of negative sentiment.  Yet again we see no comments at all made against Tara Reid, and Kerry Katona also scores very low.

How does this translate against who the public say they want to win?  We can look at this by viewing the score for the contestants against words like ‘win’ or ‘winning’.  This is shown in the figure below.

This time we can see how the scoring changes over the course of the evening.  Before the program even airs we can see that there is a fair amount of support for Jedward and Amy Childs, with Lucien Laviscount and Paddy Doherty also showing up in the analysis.

During the early part of the show in the evening, we see Jedward and Amy Childs neck and neck, with Paddy Doherty also doing well.  Sally Bercow comes through behind these three in fourth position.

The number of tweets after the show has finished drops dramatically, and we can see much smaller numbers, showing perhaps that the public are not discussing the show outside of the program.  This may have an impact on viewing figures over the whole series, since Channel 4’s Big Brother had 24 hour, round the clock viewing available through one of its sister channel networks.  Channel 5 (probably in order to reduce costs), have instead gone only with an extended highlights show, and also instead of a dedicated Big Brother website, are publishing content straight onto youtube and facebook.

The betting odds for the contestants largely tally with the findings shown above, with one or two notable exceptions.  Kerry Katona is listed as second favourite by the bookies – I suppose we should remember that she won I’m a Celebrity in 2004, so she has past experience of reality TV shows.  However in our analysis she does not show up at all.  If we look at what words do come up in context with Kerry Katona,  we see the word ‘drugs’ – perhaps suggesting that the public view her more negatively due to her recent drug problems.

However, we should also always remember that the demographic for Twitter does not necessarily reflect the demographic of the voting public – as we have seen from previous studies on X Factor, it is not always the case that the analysis found from Twitter will match the actual result of the show.  It is possible to monitor trends of individual contestants over time though, and this is something that we will look at in more detail in the coming days.

We will be continuing this analysis over the coming days and will also look to provide more in depth analysis of individual contestants, in particular why the public think a certain way, and how this changes over the course of the show.

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X Factor: It’s a ‘yes’ for Gary…but jury is still out on the girls

The first episode of the X Factor 2011 aired on Saturday, with three new judges:  Gary Barlow, Tulisa Contostavlos and Kelly Rowland, with Louis Walsh completing the panel.  So, what is the Brand Aura: discover verdict on their performance?

As we have already reported, Gary was the clear winner in the volume of tweets he received on the night.  Now, Brand Aura: discover can reveal the context behind these tweets.

Looking at the key words of Gary & Barlow, we can see that most closely connected is ‘Simon’ – Gary is clearly being directly compared to previous head honcho Simon Cowell. Gary clearly comes out well in this comparison with words like ‘best’, fancy’, twinkle’ being closely associated with him.  The words ‘Matured’, ‘curry,’ ‘line’ appear next: the tweeters are repeating Gary’s line on the show where he said to a contestant ‘In what way have you matured? Because things mature nicely like red wine and cheese. But you’ve matured like a bad curry.’  This line was included in as ‘Gary Barlow’s Insults of the Week.

Additionally, according to the Brand Aura: discover analysis, Gary seems to have already amassed a team of fans who refer to him using a nickname  – Gazza. Looking at the wordcloud for Gazza are where his fans opinion really comes into its own.  Words like ‘amazing’, ‘loving’, ‘oooh’, ‘fit’ are right up there as well as an immediate desire to group themselves behind Gary – ‘teamgary’ and ‘faircaptainbarlow’ show that the Gary Barlow fans know who they will be voting for.  Gary’s category is looking like a good bet for winning X Factor at this early stage!

Turning to the girls, the verdict is not as unanimous.  For starters, the volume of tweets for Kelly and Tulisa was significantly less than for Gary.

Looking at Brand Aura: discover wordcloud for Tulisa, it appears that most discussion was about the incident when a contestant launched a tirade of abuse directed at Tulisa and a bodyguard had to remove the contestant.  This is shown with words like ‘bodyguard’, guy’, ‘sorry’. Users on Twitter have clearly not made up their minds about Tulisa yet.

Turning to Kelly, she is clearly directly compared to other females, including Tulisa, Cheryl (a previous judge) and Frankie (from the Saturdays).  Her use of the word ‘freaking’ is highly mentioned!  More positively words like ‘love’, ‘real’, ‘liking’ and ‘personality’ show that the Twitter audience seem to be warmed to Kelly.

We can contrast the audience views of Tulisa and Kelly with that of the previous female judge, Cheryl Cole.  Looking at the words Cheryl and Chezza show that she is sorely missed.  Words like ‘miss’, ‘best’, ‘disappointed’, ‘amazing’ are closely correlated with Cheryl in the Brand Aura: discover analysis.

So, from the judges performance on the first show of X Factor 2011 and the Brand Aura: discover analysis we can say that  Gary has done a good job of replacing Simon and Kelly has had a warm response.  However no firm opinion has been made of Tulisa, and, importantly,  no-one has replaced Cheryl Cole as yet.

Note that you can repeat all of the above analysis yourself by going to, clicking on the X Factor link and searching for words in context.

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X Factor new judges – which one was the best?

We have downloaded tweets made over the weekend and looked at them in context in order to work out which of the judges the public liked the most.

The judges for this year are mostly new – with only Louis Walsh remaining from previous series – Gary Barlow (of Take That), Kelly Rowland (of Destiny’s child) and Tulisa Contostavlos (of N-Dubz) all joined as first time judges this year.

The first episode of this year’s X Factor aired in the UK on the 20th August, and we looked to analyse in context with words like ‘fave’, ‘best’, ‘great’ to see which of the judges has come out on top.

You can see our analysis in the figure below, which shows that Gary Barlow came out on top, with Tulisa and Kelly quite close to each other and Louis in last place.  It is unfortunate for Louis Walsh, being the only familiar face it is likely that little discussion of him will have taken place ahead of all the new judges, which may help explain quite how poorly he does.

Ranking of X Factor judges

Ranking of X Factor judges

We will look to do some more analysis on the X Factor and other reality TV shows in the coming days.

If you would like to know more information about Brand Aura technology, please contact

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Police used twitter and Blackberry messenger to thwart riots

A recent article on the BBC news site describes how the police used twitter to identify new targets for rioters but that very quickly they were swamped with the number of tweets and comments that were being made.

In addition, they found it difficult to sift out which comments were serious, and which were not.  If you are sitting reading the tweets as they are made then this will of course be very difficult – when the volume reaches a certain level it will be virtually impossible for anyone to be able to make sense of it.

However the analysis presented previously in our blog shows how an automated contextual analysis tool can indeed be used to make sense of the underlying data.  We were able to analyse the data on an hourly basis, and simply ask what locations are coming up in context with the word ‘next’?

The analysis presented in our whitepaper shows clearly that the locations most talked about were indeed attacked by rioters later on.  Our analysis picked up the locations discussed in the BBC article as well as other locations such as Brixton, Croydon, Walthamstow, and so on.  In almost all cases there was a  time gap of a good few hours between the location being discussed on twitter and the rioting and looting activity actually taking place.

This shows again how the use of contextual analysis on social media can be used to gather information, and indeed how powerful this approach can be.

For more information on the Brand Aura: discover tool, please contact

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Difference of context with police during London riots

Looking at the twitter data associated with the English riots, the Brand Aura:discover tool shows a clear difference in association when different terms for the police are analysed. Using the keywords ‘feds’ and ‘met’ in the keyword search in Brand Aura:discover shows the terms are used from very different perspectives. The key word ‘feds‘ is a London slang name for the police, and ‘met’ is short for Metropolitan Police.

A striking difference between the keywords is the type of language used. The keyword ‘feds’ as a slang word can seen to be closely associated with the language of the street – ‘shudda’, ‘hittin’. The keyword ‘met’ on the other hand produces very much more proper language, the only exception being ‘legit’.

Looking first at the term ‘feds’ , Brand Aura:discover shows antagonistic and violent language closely associated with this key word. ‘Fucked’, ‘banged’ ‘hittin’ ‘playdirty’ are some of the words very closely associated in the word cloud that jump out.

Other words that closely follow the key word ‘feds’ are: pple, community, watch which reflect the idea as discussed in the Guardian on Saturday that points to de-individualisation and being part of a tribe as being key. As Professor Jack Levin said of the riots in the linked article ‘it was about reinforcing a sense of community’. Our analysis certainly agrees with this theme.

When looking at the words associated with the keyword ‘Met’, a difference picture emerges. Specific politicians are named in Cameron and Clegg. Looking further at Cameron shows an extremely negative view closely connected with his name, with words like corrupt, poor and unacceptable very closely associated in the Brand Aura: discover analysis.

An interest in police procedure can also be seen here with words like operation, resources, deal and disorder closely associated with the key word in the Brand Aura: discover analysis.

If you would like to repeat any of this analysis, simply go to the weblink, click on the link for the riots data, and type in the words that you wish to analyse, such as ‘feds’ or ‘met’. Clicking on any word in the subsequent wordcloud will make it the centre of the analysis, with any words surrounding it being found in context with this word. The closer the other words are to the centre, the closer they were found in context with the particular word under analysis.  For example, another slang word for the police is ‘pigs’ – the resultant contextual analysis for this word is also interesting.

If you would like any more information about the Brand Aura: discover tool, please contact for further information.

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