Question Time

A twitter analysis
by Marie Segger

Analysis

Introduction

Twitter can be a powerful tool for politicians, journalists and individuals. With the election of Trump it can be argued that a new era of twitter, politics and journalism begins.

The present analysis should point towards a different approach to Twitter as a database that can be analysed by journalists. Fact-checking has become more important especially since the rise of fake news.

A Twitter analysis can help to bust false claims, find out who influences certain debates and if bots are distorting the public opinion.

The present analysis deals with the use of the #bbcqt hashtag for the BBC‘s talk show “Question Time“ on 8/12/2016. This particular show was selected, because the guests were Sarah Wollaston, Richard Burgon, Nigel Farage, Will Self and Louise Mensch.

In the run up to the show a discussion came up on Twitter about the high number of right-wing guests. This was determined to be a good staring position for an analysis.

Top tweeter

A co-hashtag analysis showed that users sometimes used the hashtag #questiontime or #bbcquestiontime as well. However the number proved to be so small that these tweets were not included in the data set.

The hashtag is used together with other hashtags as well, but it depends very much on the guests and topic of the show. In the present sample one example of this would be #UKIP. However we cannot conclude that all tweets using this hashtag are about the show.

Comparing the amount of tweets send from different accounts throughout the 24 hours time period shows that one account in particular stands out. Twitter user @somenath_udemy has tweeted 120 times using the hashtag #bbcqt.

The bar looks disproportionate on the chart, as the second top tweeter tweeted 14 times using the hashtag – less than a fifth of the number the top tweeter tweeted. The other bars lie close together spanning from 10 to 13 tweets.

Bots

The dimensions of the first bar chart suggest the assumption that the amount of tweets the top tweeter sent is unusual. The account could be a bot.

Analysing the top tweeters with the means of the Bot scanning programme Bot or Not? and by manually looking at the profiles two of the profiles seem particularly likely to be bots. The account of the top tweeter @somenath_udemy seems to since have been deleted. A strong sign for it to be a bot or in some other way an illegitimate account.

The account is removed from the data sample, as is the account @nojuboys which has been deleted as well. The other accounts seem to be real, even though some have a high output of tweets most of the accounts have a short profile description, a profile picture and tweet original content and/or reply to tweets.

Some accounts seem to be a combination of both – personal content as well as what seems like automatic retweets make up the profiles. As a general rule the present report considers every account that includes original content (tweets and replies) to not to be a bot and therefore these accounts are included in the sample.

With 2 out of 12 top tweets being classified as bots, this leads to the assumption that about 16% of the accounts are bots.

Ratio Retweets

Filtering the tweets in the dataset after original content and retweets shows that about 22% of the tweets are original tweets whilst 78% of the overall number of tweets during the chosen time frame are retweets. About 3,4% of the total number of tweets come from the top tweeters (not including the bots).

While a high number of retweets using a trending hashtag could hint at a high number of bots taking advantage of a trending topic, this does not seem to be the case for the present sample as a look at the tweets with the most retweets shows.

Accounts with the most Retweets

All of the top RTs are using the hashtag in the context of the BBC’s show. The most popular retweet however has more than double the number of retweets than the second most popular tweet by the account @WomenDefyUkip. The account @profanityswan is a verified account, led by Andy Dawson, a blogger and twitter personality.

The original tweet is a call to action and was send by the account days before the actual show. The tweet has since been deleted.

The second most popular tweet is a question aimed at the official Question Time account, that highlights a controversy surrounding this week’s episode of Question Time.

The person mentioned, Alison Pedley is a producer of the show who is in the hot seat for sharing content by the radical rightwing organisation “Britain First”. The viewers therefore criticise the BBC for being biased.

The sixth most popular tweet comes from the official account of the show and features a video. Two of the most retweeted tweets come from one and the same account: Jack Monroe, verified on Twitter and a journalist and writer therefore gathers an overall retweet number of 625 at the time of counting.

Overall the top retweets show that tweets from verified accounts, tweets including a video or photograph as well as tweets from accounts with a big following are most likely to get the a lot of retweets.

Location Tweets

Looking at the bar graph displaying the location users disclosed the most often (adding items such as “London” and “London, UK” up) most tweets come from places in the United Kingdom. As this is the main location the programme is broadcast and it features British politicians it seems plausible that the majority of the viewers tweet from this country.

Big cities like London, Glasgow and Manchester are featured. Surprisingly Sheffield, a city in the North of England also features on the list.

The first assumption is that it features because a lot of leave voters are watching and Sheffield overwhelmingly voted to leave the EU, one of the top topics in the debate of the show. But upon evaluation Sheffield shows up because of one the top tweeters being located in Sheffield.

Europe is another location that seems to fall out of alignment. However this might be explained by a certain number of pro European twitter users watching and discussing the overwhelmingly rightwing centered debate.

Location Profiles

The location of the profiles prove the assumption that the tweets coming from unexpected places like Sheffield, India and Europe belong to one or a few accounts. The three places drop out of the bar chart. Instead “North West, England” shows up.

This reinforces the claim that most of the show’s audience are in fact based in the United Kingdom.

Demographics

Spot-checking the accounts and analysing the profiles of the top tweeters shows that many of the profiles have a variety of themes in common. All of the profiles showed some sort of political belief or affiliations with parties, politicians or themes that are regarded as inherently right- or left-wing.

There are accounts that support the Labour party (eg. @jpjanson, @davelawson35, @louiseleelee, @BENEFITS_NEWS) and its leader Jeremy Corbyn (@BobSmithWalker, @j_sutherland2, @jpjanson). Anti-Brexit and anti-Trump motives also feature on many profiles (@vdavidmartin, @Roadwarrior29).

Equally as common are pro-Brexit, pro-Trump and rightwing parties accounts (@Bikciv, @alllibertnews, @Larterlia). Scottish themed accounts also feature in the debate.

As Scotland still plays a prominent role in the Brexit debate the Twitter accounts show that the people of Scotland do feel a strong sense of belonging and it will be interesting to see how the public reacts to further news and negotiations.

Semantics

Time One bbcqt RT Farage BBC tonight audience Producer First Britain Mensch panel Nigel UKIP week lefty job 3 real yet TV Show next like watch now Fair Self Louise wing isnt 2013 Hey two tune MP Im EU Le Fed UK far Facebook Question repeatedly right posts Alison Pedley usual balance shared Considering need rightwingers tonights Heres just asking sharing watching times complete people fucking questions Thursdays please man memes since Although Tory year also Tories Dimbleby Brexit David make Trump sure dont seat BLOODY members get NHS Wollaston thread share think little NEVER anyone rightwing bias views licence parody leader concerned supporting wont grubby tweet ludicrously plus Jack Good Former Monroe cancels 1045pm invite fringe weeks Well along Mustread packing EDL marr biased opportunists endless see history Pen know boycott Leaving NigelFarage posting pernicious saw court added force diet beyond demonstration groups earlier

Looking at the word cloud a few words stand out from the rest. First of all the hashtag of the show bbcqt is the biggest word in the cloud. Second of all the letters RT stand out as about 78% of the tweets are retweets and therefore contain the marker “RT”.

The name of the show, consisting of the words “Question” and “Time” also appears prominently in the cloud. Many of the words are to be expected, for example the name Farage, one of the biggest words as he is arguably the most popular out of the guests.

His name also appears as “NigelFarage” and “Nigel”. The same goes for the other guests on the show, “Louise” and “Mensch” also appear quite prominently in the cloud.

A bit smaller appears the names “Wollaston” and “Self” the other guests of the show’s host David Dimbleby, whose name also appears in the cloud. With Jack Monroe one of the top tweeters’ name appears in the cloud as well.

The name Alison Pedley also comes up in the word cloud. This highlights a controversy surrounding this week’s show as the producer (also featured in the cloud) shared content of the organisation Britain First (also featured in the cloud).

Another name that draws attention is, albeit split in the word cloud, Le Pen. The French politician got mentioned in a popular tweet and was a popular name people seemed to connect especially to Nigel Farage.

Besides Le Pen the only other foreign politician mentioned in the word cloud is Trump, the at the time of the show president-elect of the United States. Trump, as well as Le Pen and Farage are rightwing politicians known especially for their hard stance on immigration.

Consequently the words “rightwing”, “UKIP”, “Tory”, “Tories”, “Brexit” and “Leaving” are featured in the word cloud. The terms “EU” and “NHS” also point to a debate about Brexit and the future of the country.

The derogatory term “lefty” also appears in the word cloud, pointing towards a rightwing audience.

Looking at negative words (or swear words) in the cloud a few word stand out:

  • Fucking
  • Pernicious
  • BLOODY
  • Grubby
  • Ludicrously

The term “grubby” for example stems from one of the guests on the show and the official BBC’s Question Time account tweeted the statement as a quote:

Although the word “bloody” can have a positive connotation a look at the associated words shows that this is not the case for the present sample. “Bloody” appears for example in context of “Bloody Farage”, “undemocratic bloody disgrace” and “bloody awful to watch”.

Many viewers seem to find the discussion and the guests of the show rather controversial.

The verbs in the word cloud echo this sentiment as they are mostly negatively connotated:

  • Cancels
  • Force
  • Wont
  • Isnt
  • Dont

Most of the other verbs have a neutral connotation and stand in context of the show, eg. “watching”, “saw”, “think”. One of the few positive verbs “supporting” proves to stand in a negative context when analysing the data in detail.

The twitter user laments the apparent support of rightwing politicians by the BBC by inviting Farage for the 32nd time.

Other words that are arguably negative in the context of a political talk show are:

  • Boycott
  • Concerned
  • NEVER
  • Parody
  • Opportunists

The word “boycott” comes with two different links. Either a boycott of the BBC or its Question Time show or in context of Nigel Farage and his according to the twitter users ubiquitous TV presence.

Conclusion

The findings in this sample are not very surprising regarding the location of the tweets and accounts participating in the debate surrounding the hashtag #bbcqt. What is interesting though, is the semantic analysis and the look at the demographics.

With regard to the present analysis, the conclusion can be made that a twitter analysis is an interesting approach to examine the mood, opinion and motives of the public. There are certainly many other aspects that can be analysed depending on the sample data.

In this case an analysis of the mentions of the guest, their amount and connotation could have been an interesting idea as well. However the restriction in size does not allow this this time around.

Twitter is a tool in journalism that won’t disappear anytime soon. Even traditional institutions like the BBC academy have started to teach how to use the social media platform.

Twitter can among other aspects be handy for breaking news, crowdsourcing information and distribution of content. What this analysis shows is that Twitter can also be a powerful tool to understand the public opinion and to get an idea of who is taking part in public debates.

Twitter can be regarded “as a networked communication space that results in a hybridity of old and new frames, values and approaches” and for a journalist this space can be a source of knowlegde. Even for journalists that do not feel comfortable or do not have the time to handle big data sets, there are tools that can be used.

One example is the Bot or Not? tool by the University of Indiana. Another example is the platform HashtagNow, that explains the meaning of hashtags and often links to the origin of the hashtag.

There are many tools available, especially for time pressured journalists. If the time is no issue, it is however definitely worth it to conduct an in-depth analysis.

Contact Marie

Feel free to provide feedback, suggestions for new topics, inspiration or just say hello!

msegg002@gold.ac.uk