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Trends in twitter talk
- 1. Trends in Twitter Talk: Looking back to look forward Dr Ruth Page University of Leicester rep22@le.ac.uk; @ruthtweetpage
- 3. Self branding and searchable talk • Self branding (Marwick 2011) & micro-celebrity (Senft 2008) • Searchable talk (Zappavigna 2011) • Follower lists • Hashtags • Retweets • Links
- 4. Data sets • 30 celebrity accounts • 30 ‘ordinary’ accounts • 30 corporate accounts • 2010-11: 90, 392 tweets • 2012: 87, 343 tweets • All publically available material, all English language
- 5. Corporations • travel: @bluejet, @luxorlv, @southwestair, @british_airways, @londonmidland, @connectbyhertz, @carnivalcruise • entertainment: @directv, @marvel, @travelchannel, @tvguide • food: @sainsburys, @waitrose, @tastidlite, @popeyeschicken, @starbucks, @dunkindonuts, @wholefoods, @uktesco, @dunkindonuts • technology: @emccorp, @itunesmusic, @dellcares, @costcomcares • finance: @hoover, @hrblock, @zappos, @wachovia, @intuit • sport: @chargers, @chicagobulls • retail: @selfridges, @americanapparel, @karenmillen, @reiss, @marksandspencer, @rubbermaid, @johnlewisretail.
- 6. List of celebrities • Britney Spears, Ellen de • Ashton Kutcher, Jimmy Generes, Ladygaga, Fallon, Shaquille O’neill, Oprah Winfrey, Demi Lance Armstrong, Moore, Lilly Allen, Paris Arnold Schwarzenegger, Hilton, Sarah Brown, Stephen Fry, Dave Dita von Teese, Holly Matthews, Jonathan Willoughby, Dannii Ross, Jamie Oliver, John Minogue, Mischa Cleese, Philip Schofield, Barton, Amanda William Shatner, Andy Holden, Amy Lee, Murray, Charlie Katherine Jenkins Brookner, Boris Johnson
- 7. Status and Follower lists
- 10. Distribution of tweet types (2010) 70 60 Percentage of all Tweets 50 40 Updates 30 Addressed Messages 20 Retweets 10 0 Celebrity Ordinary Corporate
- 11. Distribution of tweet types (2012) 70 60 Percentage of all Tweets 50 40 Updates 30 Addressed Messages 20 Retweets 10 0 Celebrity Ordinary Corporate
- 12. Modified Retweets • When one member forwards a message from someone else to all their ‘followers’ • Reconfigures email forwarding • Involves two participants – Original author – Person who forwards + adds new material • Turn-taking represented in reverse order – [Retweeter’s comment] RT [original message]
- 13. An example
- 14. Modified retweets over time 7000 Relative Frequency (per 6000 million words) 5000 4000 3000 2010 2000 2012 1000 0 Celebrity Ordinary Corporate
- 15. Addressed messages and ‘politeness’ • Corporate accounts – For customer care – For social media outreach • Distinctive language use (keyness) – Thanks/sorry/please/glad • Politeness (Brown and Levinson 1987)and Face (Goffman 1959) – Face enhancing – Face threatening – Face saving
- 16. ‘Thanks’ and ‘Sorry’ • Thanks – Face-enhancing – 4668 per million words (2010) – 6444 per million words (2012) • Sorry – Face-saving – 1841 per million words (2010) – 1688 per million words (2012)
- 17. Thanks 18000 Relative frequency per million words 16000 14000 12000 10000 8000 2010 6000 4000 2012 2000 0 Messages Updates Messages Updates Messages Updates Corporate Celebrity Ordinary
- 18. Examples • First 3 people to tweet a shot of themselves wearing American Apparel nail polish win some of our new summer colors! http://bit.ly/bMvh4d – @AmericanApparel Tue, 25 May 2010 20:02 • We've got our winners! Thanks for all the great nail polish entries! Winners, we'll DM you shortly! – @AmericanApparel Tue, 25 May 2010 21:00
- 19. Thanks • As a closing formulae – Thanks + name – Thanks, BR xoxo • Thanks for the... • Thanks to X for..... – Feeback, tweeting, sharing, reaching out, your comment, letting me know, interest, posting, kind words – Patience, support
- 20. Sorry 9000 Relative frequency per million words 8000 7000 6000 5000 4000 3000 2010 2000 2012 1000 0 Messages Updates Messages Updates Messages Updates Corporate Celebrity Ordinary
- 21. Examples • @username1 Sorry to hear you feel that way. Is there any particular reason why? Can I help? – @LondonMidland Thu, 09 Aug 2012 22:05 • @username2 oh. Yikes :( Really sorry about that - did you leave the store already? – @Starbucks Tue, 24 Jul 2012 19:38
- 22. Sorry • As a closing formulae – @username3 No, we do not have pillows onboard our planes, sorry!! • Sorry about/to hear about/for... – That/this – The (bad) experience, confusion, delay, issues, (long) wait, transfers, queue, time spent, trouble, disappointment, embarrassment, f rustration, inconvenience, hold up, problems
- 23. Rise of ‘Searchable Talk’:#Hashtags • Originated as search terms used by updaters – Folksonomy • Aggregate tweets about a particular topic or event (#scd, #xfactor, #occupy, #Libya) • Idiomatic uses – Internet memes (#fail) – One-off creative expressions (#bbcwhatareyou) • Hashtags used to increase visibility via trending topics (but now search algorithms changed so not needed)
- 24. Hashtags over time • 2010 – 9490 per million words • 2012 – 15160 per million words
- 25. Hashtags in 2010 14000 Relative Frequency (per million 12000 10000 8000 words) Updates 6000 Addressed Messages 4000 2000 0 Celebrity Ordinary Corporate
- 26. Hashtags in 2012 20000 18000 Relative frequency (per million 16000 14000 12000 words) 10000 Updates 8000 Addressed messages 6000 4000 2000 0 Celebrity Ordinary Corporate
- 27. Most frequent Hashtags (2012)
- 28. Rise of ‘Amplified Talk’ Percentage of Updates with a link 80 70 60 50 40 2010 30 2012 20 10 0 Celebrity Ordinary Corporate
- 29. Collapse of professional/personal 2010 2012 • Celebrities • Celebrities – More ‘backstage’ shots – Material about themselves – More ‘personal life’ photos – Backstage access – ‘Gossip’ and ‘jokes’ – Promotional material (e.g. • Ordinary Competitions) – Some still reflect professional identity • Ordinary – But ‘personal life’ photos and – Articles in their field general interests (fashion, gardening, films, food, sp – Own blogs ort) • Corporations • Corporations – Own web sites – Own web sites – Audience engagement through – Promotional offers photosharing – Charitable work
- 30. General trends in links • Multimodal – Photos, video • Multi-platformed – Facebook groups, Google plus – Pinterest – Tumblr – Instagram, Daily Booth, VintageCam, Yfro g, Whosay – Mobile Apps
- 31. Conclusions – the way forward? • Make your talk searchable • Enrich and amplify your talk • Increase face-enhancing interactions • Increase your reach across platforms • Increase authenticity (in a professional way) • We will see.....drop back in 2014
Editor's Notes
- Begin with the context of TwitterTwitter is now well known as a mainstay of Internet useBecame mainstream in 2009Debates about how fast it is still growing, (one report suggests that it’s growth is exponential and in 2011 increased by 32%, while a recent Pew Internet Survey suggested that 15% of the US population now use Twitter in 2011).From a marketing/PR perspective, Twitter is notable as a form of Electronic Word of Mouth, where harnessing the power of talk on Twitter can predict box office success or the outcome of political electionsBut as this image of the shares on the stock market suggests, Twitter also functions like a linguistic market place.Far from the early rhetoric of web 2.0 which characterised social media in contrast to its predecessors in e-commerce and stressed its new, collaborative and democratic structures, the participatory culture that was heralded by critics like Henry Jenkins has not always been evenly distributed. Instead, the members of Twitter operate within an economy which prizes attention and visibility
- The priority of attention and visibility underpin the processes of self branding and micro-celebrity which have been described by the sociologists Alice Marwick and TereseSenft. From this perspective, self representation is a commodity which can be consumed by others, and an audience is perceived primarily as a fan base who need to be maintained and cultivated through strategic interaction.That strategic interaction is embedded in a parallel trend, which Michele Zappavigna describes as the development of ‘searchable talk’. Here conversational exchanges are important not only to the immediate participants involved in the exchange, but are also used as a resource by others (for example, data mined by analytic searches or sold on to advertisers).Talk is valuable in Twitter: your value is not just self representation, but how you interact with others.There are many linguistic features that operate within this value system: the size of a follower list, the use of hashtags, retweets or linked material can all contribute to the perception that a given Twitter member has more status than another (though of course their actual influence is another matter altogether).Differences in the size of follower lists, use of hashtags, retweets and links suggest that Twitter is a highly varied environment, and that those differences reflect and reinforce offline hierarchies based on social and economic power. My own work has compared the Twitter behaviour of celebrities, corporate accounts and personal accounts that publish updates and messages in the public timeline of Twitter. My talk today builds on that work, but extends the earlier analysis with a longitudinal comparison. In tracing the trends in these resources used typically in the processes of self branding and micro-celebrity, I’ll suggest which factors seem most likely to continue as promotional strategies in Twitter for different groups of members.
- One of the ways that status is perceived in Twitter is the relative size of the follower list on a member’s account. The size of that list can vary considerably. So here are the lists of two Twitter members – can you guess who they might be from this detail?
- The trend that we saw with the individual example is borne out by the aggregated following and follower lists for the celebrity and ordinary accounts.You might notice from the figures in the table that for all accounts, the Follower list tends to be larger than the list of people that the member follows, but that the scale of that difference varies, and is more marked for the celebrity accounts than any other type.We might also notice some other features from the figures in this table:Follower lists increase more than Following lists do (in fact, the Celebrity ‘Following’ average decreases slightly)The rate of growth is actually the same for celebrity and ordinary Follower lists: both have tripled in size over two years. But because of the disparity between following and follower lists, the differences in the ratios over time change much more dramatically.I haven’t got comparative data from the Corporate profiles from 2011, so I can’t comment on their rate of growth, but you can see that the follower list size is significantly greater than the average ordinary account, though not reaching the size of celebrity audiences.So celebrity fan bases in Twitter seem to be increasing exponentially, and faster than the increase of ordinary audiences, or indeed the rate of growth of Twitter itself.
- The scale of the audience also influences the kinds of interactions that take place on Twitter. In this analysis I make a broad distinction between:Updates – one to many broadcasts published on the public timelineAddressed Messages – public messages which are directed to named Twitter users (and begin with the @username) – these are distinct from the private DMs which are not included in my analysis (and were not collected)Retweets: updates or messages which have been forwarded without modification by the recipient of the original
- In 2010, the aggregated distribution of types of tweet show that for all 3 groups, the preferred type of tweet is the update, or the 1-to-many broadcast. However, this preference is more marked for the celebrities and least marked for ordinary twitter users.This difference is perhaps understandable: it is more economic for a celebrity to publish a single update to their sizable fan base than to write individually addressed messages to all of their followers.
- In 2012, this communicative pattern continues for the Celebrity and Ordinary accounts, but not for the corporations. The pattern reverses here and Addressed messages account for a greater proportion of the posts that are published.This is quite striking, especially if we compare it with the modified retweets that are found in the updates.
- So modified retweets are like conversational snippets, but rather than just being directed to a single person, are broadcast to entire follower lists. On the one hand, this projects the image of the updater as engaged with their audience, but also affords them the opportunity to Retweet endorsements from their fans or customers
- This chart shows the relative frequency of modified retweets in the updates posted by Celebrity, ordinary and corporate accounts. As you can see, the frequency of modified retweets decreases in both celebrity and ordinary updates, though much more markedly for the celebrity accounts. At first, I thought this might be because of the ‘quoting’ option that has been added to Twitter. But a search through the updates showed that this was only being used by one or two updaters and then only infrequently. And in the same period, we see modified RTs increasing in the updates from Corporate accounts. It would seem, on the surface of things that celebrity communication on Twitter is becoming less like a conversation, while conversely, corporate accounts in this data sample at least, are using Twitter more than ever to engage with their audiences. This begs the question: what kind of talk is happening in the addressed public messages? And why might this increase?
- One reason why dialogue found in the ‘addressed messages’ occurs much more in the corporate accounts than the celebrity accounts is because these accounts in many cases function as customer care accounts: they are the public channels available for customers to post queries/complaints/feedback and to get a prompt, public and personal response from the company. NB this doesn’t explain why the ‘ordinary’ accounts don’t have a similar balance between updates and addressed messages.So to examine the qualities of the customer care talk, I began by looking at the frequency word list for each set of addressed messages and identifying the content words that occurred disproportianately often in each case (in linguistics, this is described as the keyness of items). In the addressed messages from corporate accounts, the content words which were strikingly key included: thanks (and its variants thank you/thank/thnx), sorry, please and glad. We’ll look at those items and the actual contexts in which they occur in a minute, but I want to begin by thinking about the function that those words might serve.The items please/thanks/sorry all belong to the lexical set of what in common sense terms we would describe as ‘politeness’ (remembering to say please, thank you and ‘may I leave the table’). In linguistics, the definition of politeness goes much further than these formulae. Brown and Levinson describe politeness in terms of the speaker’s ‘face’[. Here they don’t mean your physical ‘face’ but rather the self image that we refer to when we use phrases like ‘to save face’: the projected image of self that the sociologist Erving Goffman described much more in his influential works of the 1950s and 60s. So what I am interested in exploring for a few minutes here is what those formulae of ‘please’ and ‘thank you’ do to the identity or face that the corporate accounts are projecting through these addressed messages.It’s helpful here to distinguish between the different aspects of what B&L describe as ‘facework’. They point out that interaction can be face-enhancing – it can positively build your identity or encourage solidarity between speaker and hearer (e.g. Compliments). Conversely, interactions can be face-threatening – we can make ourselves look foolish, less than perfect or talk to people in a way that imposes on their intentions and/or causes disharmony (e.g. Giving orders, criticising or making a complaint). When those face-threatening moments of interaction occur (B&L call this a face threatening act), then the speaker has the option of using face-saving strategies (apologising, using mitigating strategies like hedges or humour).So we can distinguish between the different roles that thanking might have (implied face-enhancing strategy) compared with apologising (a face-saving strategy) or the face-threatening nature of requesting something from another (indicated by ‘please’).The question is: what kinds of politeness occur most often in the addressed messages, and how does this vary between user groups and over time?
- If we take ‘thanks’ and ‘sorry’ as our starting point, we can see that if we look at the overall picture (so corporate, celebrity and ordinary data sets, both updates and addressed messages) then there is a pattern:The face-enhancing language of ‘thanking’ occurs more often than the face-saving language of saying ‘sorry’ (over twice the frequency)And that the face-enhancing language of thanking increases between 2010 and 2012, while the face-saving language of apologising decreases (though less sharply) over time.
- This chart shows the relative frequency of the word ‘thanks’ (and its related variants thank you, thnx) disaggregated by user group and time.What we see is that for all user groups, ‘thanking’ occurs more often in addressed messages than in updates for all groups, and all groups show an increase in the ‘thanks’ that occurs in the messages (though not always in the updates).The frequency of thanking also varies user group, where corporations offer thanks most often, and ordinary accounts the least
- This chart shows the relative frequency of the word ‘sorry’ across the different user groups and over time. What we can see very clearly is that, like ‘thanks’, sorry occurs more often in messages than updates: its a linguistic behaviour that is aligned with one-to-one communication, not a mass broadcast. And we can see that the group that uses this face-saving behaviour most often is the corporate accounts, but for all three groups, the practice of saying ‘sorry’ seems to be declining in this data set at least.
- So to return to the comparison between Thanks and Sorry, what does this suggest about trends in Twitter talk? Is that less things are going wrong and so there is less need to apologise?More likely that face-enhancing behaviour is increasing (a positive strategy for building reputation), and thanks reflects the communicative contribution (so more time is being spent acknowledging the messages that are being sent to the accounts)
- What we see from these two charts is thathashtags tend to occur most often in Updates, rather than in addressed messages, and that the use of hashtags has increased for corporate accounts the most, but that celebrity use of hashtags has also increased (especially in updates) so that the need to make their talk searchable now outstrips that of ordinary Twitter users.
- When we look at the hashtags which occur most frequently in the 2012 dataset, we can identify the following trends:Celebrities use hashtags which foreground their products or performances (Dancing with the Stars, Australia’s got Talent, Late Night Show, The Voice), This is Love / Katy Perry 3D, while corporate accounts use hashtags to foreground company names (EMC, Rubbermaid, Marvel, SelfLondon, Direct), or the topics with which the brands are associated (sales, marketing) or catch phrases (Onthefly and Homeadvantage). Ordinary accounts more often use hashtags to align their tweets with a conversation (often about at TV programme or sports event – bbcqt, xfactor, wimbledon) or about events they are participating in (ales204 = module course code, csmc = cornwall social media cafe). This positions the celebrities and corporations as producers of content, while ordinary accounts are still members of the audience who are consuming a product (allbeit, making their participation in the event more visible).
- Twitter is not just a sophisticated search engine, it is also a forum for amplifying messages by linking to other content. I’ve argued elsewhere that this returns to the original function of blogging as a means of filtering content by promoting certain websites, and that the kinds of material that people link to reflects their interests (usually their professional interests) and are a means by which they establish their online reputation as ‘recommenders’ or ‘authorities’ in particular fields.
- I examined 100 links from each of the data sets (randomly selected): 600 links in total. So the trends that I am talking about here are not empirical comparisons of quantity, but more general observations.What we see is that in 2010 the material that celebrities, ordinary accounts and corporations linked to were tightly tied to the professional interest of the member (of course for celebrities, that professional interest is themselves, their products and performances). But in 2012, this has started to be diluted by more ‘personal life’ reflections. So celebrities include more ‘personal life’ photos – although this shades very closely into professional/backstage content (e..g shots of Andy Murray training, Amanda Holden watching the Olympic torch, Will.i.am carrying the olympic torch). For ordinary accounts, some members still link to content almost entirely about their professional identity (e.g. Vicar links to online sermons, debates about legalization of gay marriage etc.; baker to photos of their products or recipes; creative artist to their blog and Facebook group page), but increasingly links were to photos from days out, places visited, and to items of general interest (fashion, gardening, films, food and sport). In 2010, I could have guessed the person’s profession from their links, in 2012, I wasn’t able to do that anymore.Corporations don’t link to personal content, but the content is more personalised in that there were an increased number of links to material provided by customers (e.g. To photos of themselves wearing an item of clothing, eating a type of food etc.) or like Real Carnival Breeze to a ‘fake video diary’ of an imagined customer’s travels, or SouthWest Airlines ‘On the Fly’ videos of their staff engaging with customers in positive and funny ways.