JCPR Twitter Index


JCPR Twitter Index


It’s no surprise that Twitter has reached its tipping point when the number of techies and marketing-folk are easily outnumbered by celebrities using the platform. No longer do I have to start a conversation explaining what Twitter is, suffice to say – everyone knows.

It’s common knowledge that the UK’s own laureate Stephen Fry is a great advocate of this medium but who would have realised that Philip Schofield was more influential than Downing Street.

When I published the Social Media Index with David Brain that attempted to rank an individual’s presence across all platforms, we received a huge amount of feedback. A great deal of this focused on the fact that what we were listing was popularity and not what is more important which is influence or engagement. The resulting white paper on distributed influence tried to remedy this by analysing measurement in far greater detail.


Understanding that this is also going to ‘ruffle a few feathers’, I have been helping my colleagues at our consumer arm, JCPR, to apply the principles of SMI to the world of Twitter. The JCPR Twitter Index has been created to list individuals based upon their influence (and not like other tables, their popularity).

Influence can be measured on Twitter using the following formula:


(A full explanation of this is shown in the methodology at the bottom of this post).

What I find truly interesting is how an individual’s ranking is completely changed dependent upon whether we are looking at popularity or influence.

For example: Al Gore is rated as the 23rd in the world based upon the number of followers he has. Honestly though, how influential is he? For a man who has only tweeted 29 times (and not within the past 6 months) – I would say…not at all.

If I was to spend my money trying to get a person to endorse a company I would instead focus on the person who was far more engaged and who other people found interesting. Jonathan Ross in this case would be a great example.

I have listed three tables below, the first of these is the list of top twitters weighted by popularity, the second is by influence and the third by engagement. The full list of top 200 (celebrity) twitters are located at the bottom of this post and on the JCPR site.

Top 20 Twitters Weighted by Popularity, Influence and Engagement

Rank Weighted by Popularity   Weighted by Influence   Weighted by Engagement
1 Ashton Kutcher   Jonathan Ross   Jonathan Ross
2 CNN   Perez Hilton   Jason Bradbury
3 Britney Spears   Stephen Fry   Alan Davies
4 Ellen DeGeneres   Ashton Kutcher   Perez Hilton
5 Twitter   Graham Linehan   Adam woodyatt
6 Barack Obama   Demi Moore   Rick Sanchez
7 Brian Dooley   CNN   Philip Schofield
8 Jimmy Fallon   Lance Armstrong   Dave Gorman
9 Shaquille O’Neill   New York Times   Yoko Ono
10 John Mayer   Will Wheaton   Neil Gaiman
11 New York Times   Shaquille O’Neill   Demi Moore
12 Lance Armstrong   Downing Street   Danny Wallace
13 Henry Dartnall   Jason Bradbury   Graham Linehan
14 Demi Moore   Philip Schofield   Jenni Falconer
15 Lizo Mzimba   Soulja Boy   Karl Rove
16 Perez Hilton   Jimmy Fallon   Andi Peters
17 Dan Tetsell   Barack Obama   Britney Spears
18 P Diddy   John Mayer   Stephen Fry
19 Coldplay   Michael Arrington   Dave Matthews
20 Ryan Seacrest   Ryan Seacrest   Coldplay

Even though this is a bit of fun, there is a serious side behind it. We are always trying to help our clients understand the influence that certain people have over particular sections of society. Behind all the glitz and glamour that goes with fame, it’s important to understand where real influence lies, which is often very different to mere popularity. The JCPR Twitter Index helps us define that within the hugely dynamic social media space.

Of course, this index has initially been used to score celebs but its methodology can easily be used to look at other segments (from analysts, musicians, politician and brands). I hope to be publishing the analyst version of this very soon.

As a final point, I know that when discussing this people tend to be far more interested in ‘influence’ rather than engagement. My view was nicely echoed by AdAge when commenting on Ashton Kutcher’s use of bill board advertising when trying to win the (in)formal ‘first to 1million followers’ against CNN competition. In this piece they quoted a New York commenter who goes by Stevewax:

Seems to me what’s useful with Twitter is creating a small, two-way community with people who aren’t busy running a Twitter team and who have time to SHARE ideas. Rather than broadcast them.

Just as PR has gone to public engagement, and AR has gone to analyst engagement, it is only natural that I believe that instead of mass-broadcast (shown by popularity) or mass-amplification (shown by influence), I believe that the purest form of interaction is via multiple targeted micro-conversations where people actively engage and interact with the community. This is why when scores are weighted for ‘engagement’ the ‘involvement index’ is given the largest priority. Additional commentary on this to follow in future posts.



JCPRTI JCPR Twitter index Rg Range assigned to score
Fo Number of followers Fg Number users following
Up Number of updates @U Number of name pointing
Rt Number of retweets Ta Twitalyzer score
TaN:S Twitalyzer noise to signal ratio Ti Twinfluence score
Tg Twittergrader score Ii Involvement index score
Vi Velocity index score w Weight assigned to each attribute
Z Standardised score p Popularity
e Engagement i Influence

Following – Twitter lists the number of people each user follows. The tendency for most celebrities is to only follow a few individuals – the more people that someone follows, there is an increased likelihood of them actively participating in conversations with the community instead of simply broadcasting to it. Following ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 30) that was used as part of the algorithm.

Followers – Twitter lists the number of followers each user has. Like subscribing to a feed, this is a clear indication of ‘popularity’ as it requires someone to actively request participation. Follower ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 50) that was used as part of the algorithm.

Updates – How often does someone update what they are doing. This number is purely objective as it scores someone highly no matter what the content of their post (i.e. how relevant is it). Nevertheless it is assumed that if someone posts frequently but has poor content then their ‘followers’ will decrease. Update ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 30) that was used as part of the algorithm.

Name Pointing – e.g. @name – How many people engage in conversation with a celebrity or point to their name. The clearest way to establish this is to run a search on the number of people who reference @username in a message. This calculation is based upon a one month period combined with a 24 hour period. The number of times this happens is calculated with each range was assigned a number (0 to 30) – again this was then used as part of the algorithm.

Retweets – Has a tweet caused sufficient interest that it is worth re-submitting by others? Despite a great deal of ‘noise’ (i.e. posts that are not relevant or interesting), when someone sees something that is of high interest, their post can be re-tweeted. The clearest way to establish this is to run a search on the number of people who reference RT @username in a message. This calculation is based upon a one month period combined with a 24 hour period. The number of times this happens is calculated with each range was assigned a number (0 to 50) – again this was then used as part of the algorithm.

Twitalyzer – “This is a unique (and online) tool to evaluate the activity of any Twitter user and report on relative influence, signal-to-noise ratio, generosity, velocity, clout, and other useful measures of success in social media.” This 3rd party tool is a useful method to combine automated metrics dependent upon criteria within posts and publicly available numbers. Where tools such as this are available, we incorporate them into the algorithm to achieve a more confident score. Twitalyzer gives users scores from 0 to 100. Ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.

Twitalyzer noise to signal ratioSignal-to-noise ratio is a measure of the tendency for people to pass information, as opposed to anecdote. Signal can be references to other people (defined by the use of "@" followed by text), links to URLs you can visit (defined by the use of "http://" followed by text), hashtags you can explore and participate with (defined by the use of "#" followed by text), retweets of other people, passing along information (defined by the use of "rt", "r/t/", "retweet" or "via"). If you take the sum of these four elements and divide that by the number of updates published, you get the "signal to noise" ratio. Twitalyzer gives users scores from 0 to 100. Ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.

Twinfluence RankTwinfluence is an automated 3rd party tool that uses APIs to measure influence. For example: “Imagine Twitterer1, who has 10,000 followers – most of which are bots and inactives with no followers of their own. Now imagine Twitterer2, who only has 10 followers – but each of them has 5,000 followers. Who has the most real "influence?" Twitterer2, of course.” As with Twitalyzer, this index uses 3rd party tools to add greater confidence in the overall Twitter score. Similar to the other criteria, ranges were determined (i.e. less than 20, less than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.

Twitter GraderTwitter Grader is the final automated tool to add greater confidence to the final index. This site creates a score by evaluating a twitter profile. Similar to the other criteria, ranges were determined (i.e. less than 20, less than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.

Involvement Index – As the only personal subjective measure in the algorithm, opinion points were assigned to each celebrity. People who scored highest in this category had frequent, relevant, high-quality content that actively involved the twitter community (asking questions, posting links or commenting on discussions) and did not purely consist of broadcasting. Ranges were determined (i.e. less than 20, less than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.

Velocity Index – As more people engage on Twitter, it may become harder to keep activity going. The velocity index measures changes on a regular basis and assigns a score based on increased or decreased participation. Ranges were determined (i.e. less than 20, less than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.

Weighting Each specific variable listed above was given a standard score out of 10. Using a weighting scale I varied the importance of the each metric to establish an individual’s total score.

Weighted for Popularity – the key variable is the number of people someone has following them. There are many online tools that show this such as Twitterholic.

Weighted for Engagement – the key variables are an individual’s participation with the Twitter community (as measured by the Involvement Index), with additional emphasis on the frequency of people name pointing an individual (via @username), the numbers of followers and the signal to noise ratio. Other attributes were included in the final score but were given a lower weighting.

Weighted for Influence – the key variables in this instance is a combination of the number and authority of someone’s followers together with the frequency of people name pointing an individual (via @username) and the how many times and individuals posts are re-tweeted. Other attributes were included in the final score but were given a lower weighting.

Criteria for inclusion – There are many lists of top celebrities on Twitter – every one of these use ‘popularity’ as its main criteria. Edelman have used all these lists (such as The Times, Celebrity Tweet and Mashable together with selected and ‘interesting’ names from the top 100 from Twitterholic and used its algorithm to establish their influence.

Top 200 (Celebrity) Twitters – Weighted by Influence

Rank Name Country Segment
1 Jonathan Ross UK TV Presenter, Comedian
2 Perez Hilton US Celeb blogger
3 Stephen Fry UK Comedian, Actor, TV presenter
4 Ashton Kutcher US TV Presenter, Actor
5 Graham Linehan UK Sitcom writer (Father Ted, Black Books, The IT Crowd)
6 Demi Moore US Actress
7 CNN US News Service
8 Lance Armstrong US Cyclist, sport
9 New York Times US News Service
10 Will Wheaton US Actor
11 Shaquille O’Neill US Basketball player, Actor, sport
12 Downing Street UK UK Govt, politician
13 Jason Bradbury UK gadget Show host, journalist
14 Philip Schofield UK TV Presenter
15 Soulja Boy US Rapper , music
16 Jimmy Fallon US Comedian
17 Barack Obama US US President, politician
18 John Mayer US musician
19 Michael Arrington US Tech News Service
20 Ryan Seacrest US TV Presenter, Radio DJ
21 Greg Grunberg US Actor, Heroes. TV
22 Alan Davies UK Comedian, Actor, TV presenter
23 Karl Rove US Political advisor
24 Twitter US Micro Blogging Platform
25 Rainn Wilson US Actor
26 Felicia Day US Actor
27 Michael Black US Comedian
28 Russell Brand UK Comedian, TV Presenter, Actor
29 Neil Gaiman US Author
30 Yoko Ono US Artist ,
31 Mariel Hemingway US Actor
32 Coldplay UK Music band
33 Rick Sanchez US American TV news anchor
34 John Hodgman US Comedian
35 Fred Durst US Musician
36 Phil Jupitus UK Comedian, radio show host
37 Will Carling UK Ex England rugby captain, sport
38 Adam Woodyatt UK Actor, Eastenders
39 BBC Click UK BBC News service
40 Snoop Dogg US Rapper , music
41 Imogen Heap UK Musician
42 P Diddy US Record producer, rapper, entrepreneur
43 Brent Spiner US Actor
44 Tony Hawk US Professional Skateboarder, sport
45 Britney Spears US Singer, Music
46 Dave Matthews US Musician
47 Brea Grant US Actor
48 Penn Jillette US Magician
49 Joe Trippi US Political Adviser
50 John Cleese UK Actor, Comedian
51 Oprah Winfrey US TV show host
52 Warren Ellis UK Writer
53 Jenni Falconer UK TV presenter
54 Fearne Cotton UK Radio DJ, TV Presenter
55 Ellen DeGeneres US TV Presenter, Actress
56 Jon Favreau US Film Director
57 Jimmy Carr UK Comedian, TV Presenter
58 Hedi Monatag US MTV reality star
59 Jane Goldman UK Jonathan Ross’ wife, writer
60 David Lynch US Film Maker
61 Tim Lovejoy UK TV Presenter
62 Mike Skinner UK TV Presenter
63 Andi Peters UK TV Presenter
64 James Gunn UK Comedian, writer
65 Pete Wentz US Musician
66 Dave Gorman UK Comedian, writer, TV show host
67 Richard Branson UK Owner of Virgin Group, Entrepreneur
68 Mathew Horne UK Comedian, Actor, TV presenter
69 Martha Stewart US Entrepreneur; TV and magazine personality
70 Robert Llewelyn UK Actor, writer, TV presenter
71 Al Gore US American politician
72 Eddie Izzard UK Actor
73 Suzi Perry UK Gadget Show Presenter
74 Krishnan Guru Murthy UK C4 News Presenter
75 Travis Barker US Musician
76 Chris Moyles UK Radio DJ, TV Presenter
77 Al Yankovic US Comedian.
78 Paul Daniels UK Professional Magician
79 Danny Wallace UK Journalist, author, script-writer, producer
80 Xzibit US Rapper, TV Presenter, music
81 Rob Brydon UK Actor, Comedian
82 Calvin Harris UK Musician
83 Paulo Coelho Brazil Author
84 50 Cent US Rapper , music
85 Miley Cyrus US Actor
86 Tom Felton UK Actor
87 William Shatner US Actor
88 Rory Cellan-Jones UK Journalist, Broadcaster
89 Jamie Oliver UK Chef
90 Solange Knowles US Singer , music
91 Bill Bailey UK Comedian
92 Bjork Iceland Singer , music
93 Toby Young UK Journalist, Broadcaster
94 Stan Collymore UK Ex-footballer, radio show host, sport
95 Kevin Smith US Film Director, Actor
96 Ben Goldacre UK Scientist, journalist
97 Arnold Schwarzenegger US Governor of California, former actor
98 David Hewlett US Actor
99 Richard Bacon UK TV Presenter
100 Tony Gardner UK Actor
101 Alexander Armstrong UK Comedian, writer
102 Emma Kennedy UK Actor, writer
103 Beverley Knight UK Singer, music
104 Matt Lucas UK Comedian, Actor, TV presenter
105 Richard Herring UK Comedian
106 Charlie Brooker UK Columnist, Writer
107 Annie Mac UK DJ
108 Tim Westwood UK DJ
109 Claudia Winkleman UK TV personality
110 Chris Addison UK Comedian
111 Alan Carr UK Comedian, TV Presenter
112 Scott Mills UK Radio 1 DJ
113 Aleksandr Orlov UK Comparethemeerkat
114 Rob Corddry US Comedian
115 Kim Kardashian US TV star
116 Hillary Clinton US Politician
117 Peter Andre UK Singer, music
118 Holly Willoughby UK TV presenter
119 Tim Minchin Australia Comedian, musician, actor
120 Taylor Swift US Singer, music
121 David Mitchell UK Comedian, Actor
122 Iain Lee UK Comedian
123 Katy Perry US Singer, music
124 Peaches Geldof UK Celeb daughter
125 Mark Kermode & Simon Mayo UK Radio
126 Edith Bowman UK Radio DJ, Presenter
127 Boris Johnson UK Politician: Mayor of London, Columnist
128 Janina Gavankar US Actor
129 Robert Webb UK Actor, Comedian
130 Sara Bareilles US Singer, music
131 Michael Phelps US Swimmer , sport
132 Brett Gurewitz US Musician
133 Kate Hewlett US Actor
134 Tom Harris UK MP, politician
135 Rufus Hound UK Comedian
136 Huew Stephens UK DJ, TV presenter
137 Lady GaGa US Singer , music
138 Graham Coxon UK Musician
139 David Schneider UK Comedian, actor, writer
140 Reggie Yates UK Radio DJ, TV Presenter
141 Brooke Hogan US Singer, music
142 Mandy Moore US Actor
143 Kelly Clarkson US Singer , music
144 John Thompson UK Actor, comedian
145 David Baddiel UK Comedian, TV presenter
146 Liam Gallagher UK Musician/Singer
147 Jamie Cullum UK Musician
148 Shanna Moakler US Musician
149 Heidi Range UK Singer/Sugababes, music
150 Vanessa Hudgens US Actress, Singer, music
151 Josie Long UK Comedian
152 Demi Lovato US Musician
153 Adam Buxton UK Writer/Comedian
154 Declan Curry UK Business journalist/BBC TV Presenter
155 Andy Murray UK Tennis Player, sport
156 Hugh Jackman Australia Actor
157 Elizabeth Banks US Actor
158 Ben Miller UK Comedian, writer
159 Dan Tetsell UK Comedian, writer
160 Melora Hardin US Actor
161 Regina Spektor US Musician
162 Mark Watson UK Comedian
163 Kyran Bracken UK Sports – rugby
164 Katherine Parkinson UK Actor
165 John Prescott UK Politician, Former Deputy Prime Minster
166 Brian Dooley UK Comedian, writer, TV show host
167 Robin Williams US Comedian, Actor, TV presenter
168 Armando Iannucci UK Writer, comedian
169 Lee Unkrich US Director, entertainer
170 Katie Price UK Model
171 Ronan Keating Ireland Singer/Boyzone , music
172 Billie Piper UK Actress
173 Rumer Wilis US Celebrity Daughter
174 Alexandra Burke UK Singer , music
175 Judge Jules UK DJ, TV presenter
176 Will Self UK Writer/Comedian
177 John McCain US Politician
178 Lauren Conrad US MTV reality star
179 Neil Innes UK Comedian, writer
180 Lizo Mzimba UK Journalist, Broadcaster
181 Jamie Oliver UK Musician
182 Raef Bjoyou UK TV personality – The Apprentice
183 Miranda Hart UK Comedian, writer
184 Henry Dartnall UK Musician
185 Hulk Hogan US Retired Wrestling Legend, sport
186 Lily Allen UK Singer , music
187 Selena Gomez US Actor
188 Joe Biden US US VP, Politician
189 Alex Zane UK TV presenter
190 Drew Pinsky US Dr. Drew TV Star
191 MC Hammer US Rapper, Musician
192 Mischa Barton US Actress
193 Steve Coogan UK Comedian, writer
194 Jusint Lee Collins UK TV presenter
195 Tom Green US Actor, comedian, writer
196 Graham Norton UK Comedian, TV Presenter
197 Alexa Chung UK DJ, TV presenter
198 Gail Emms UK Sport, badminton
199 Dave Berry UK TV Presenter
200 Lethal Bizzle UK Musician

As with previous measurement posts I have published, I welcome the community to comment on it and provide your feedback.


28 Responses to “JCPR Twitter Index”

  1. Jonny, this is an amazing piece of work. Terrific insights! Thank you.


    Can’t wait to see that… 🙂


  2. Sorry, that reference in brackets, from your post, didn’t take. It was:

    “I hope to be publishing the analyst version of this very soon.”

  3. This is well done. You should also check out for measuring Twitter influence.

  4. 4 Mark

    wow….and to think I used to think I had too much free time on my hands =)

  5. First of fantastic article, and a great read

    but quick question, now did Gail Emms get ranked as No5 on the ‘Weighted by Popularity’ list? I don’t have a problem with her being No5 as I used to live in Milton Keynes and played Badminton, even went to the National Badminton Centre a few times. but she is only folowing 21 people, with 210 following her, and she has tweeted 27 times. I think some thing may be a miss somewhere. If it sorts it self out before you read this I have a screen cap I can send you. Apart from that a good, and very useful list, so many thanks for taking the time it took to do.

    Oh and congrats to Gail Emms for doing the London Marathon in 3hrs 47, a good couple of days quicker than I could do it.

  6. 6 alex

    Is this an April Fool or can I post about it ?

  7. hi

    SteveintheUK – thanks for heads-up about Gail Emms – have corrected the table so the post is up-to-datea gain now.

    Alex – even though this is a bit tongue-in-cheek (especially the formula), there is a serious side to it. We always will need to understand who is popular or influential or engaged. Please feel free to write about it – I look forward to seeing your thoughts.

  8. HI, Jonny, this is amazing! Is there anyway I could get respondent-level data (anonymized, of course, no names, just randomly assigned numeric ID)? I would love to run some regression and other analyses to see how composites of your score (number of followers, updates, etc.) are inter-related? i will be more than ok to submit all results to you or write a paper together.. drop me a line at modernmetrix at gmail dot com if u r interested!

  9. … popular, infleuntial, engaged … wow, you guys have got WAY to much time on your hands … and I mean that literally .

    Everyone belly aches about what is WRONG with America … well, might I posit that somewhere along the line MEN stopped using their ENTIRE HANDS?

    They just started twiddling their thumbs …

    Analyizing ‘zeitgeist’ is ALOT more then just tabulating ‘numbers’ … If you’re trying to get a reading on the NEXT BEST “HOT” THING … you gotta walk away from your machines … Seriously.

    This is just pablum for the peeps … Nothing here of any TRUE, REAL or LONG LASTING significance … imho.

    Love & kisses,

  10. What does the “standardized score” Z entail?

  11. Thanks canadada

    There is a serious point to all this. You may think that the time I have spent on this is wasted but there are many companies who are considering working with individuals to help endorse them. in this situation, should they work with Ashton Kutcher just because he is popular or should they instead form a relationship with a person who can engage with small yet relevent segments and can influence them.

    • Jonny, I did understand that … kinda patently so. That’s what ‘stunned’ me … cuz, yes, twitter is gaining ground WITHIN a certain PUBLICITY SEEKING set.

      Meanwhile, America is twirling off into Nothingville and this kind of thing just aids and abets same.

      Some pulbic ‘personas’ are SO OBSESSED with their “fame” they’ll do ANYTHING to feed their never-ending narcissistic impulses. Lenny Kravits posting his butt on twitter is a prime example. I mean, SERIOUSLY, who gives a rat’s ass? Well, apparently OTHER narcissistic “famed obsessed” ‘personalities’ do … And so, it all quickly becomes a breeding ground for Self obsessed ‘Publicity seeking’ inbreds.

      Meanwhile, America, WORKING America, is supposed to BELIEVE in these people? WORKING America is supposed to FOLLOW these people? Come on, this and they are NOT the manifestation of ‘the American Dream’. Rather, they are more representative of yet another ‘cloud cluster’ of the emerging American NIGHTMARE … (lest we forget – ‘Corrupt Wall Street’, ‘Corrupt Banks’, ‘Corrupt Oil oligarchy”, ‘The American DEBT’, ‘Bloated Auto Industry’. etc, etc., .. )

      Publicity for PUBLICITY’S SAKE is fluff, and fluff is just that, fluffy fluff.

      YOU, dear Jonny, MAY make some dough off your analysis, and more power to you and your ENTREPENEURIAL SPIRIT, but for the rest, and for WHAT IT intrinsically IS, well, imho, it’s about as ‘important’ as a paper clip … and THAT is not GOOD for the what was the once Great U.S. of A.

  12. Thanks Hannah

    It is essential to have a standardised score to ensure that the final number that an individual is given is not biased.

    To explain in a bit more detail…

    For example, if someone has between 4,000 and 5,000 followers I may give them a score of 7 out of 50. Ashton Kutcher would probably get 50. This range principle is applied across all the different variables (such as number or retweets, posts etc). However, if I merely added up the different numbers it would give an unfair bias towards ranges where the total possible score is very high. I therefore divide each possible variable so that the total possible score for each item would be out of 10. This is the z-score or standardised score.

    I can then apply weighting to each variable to give a final number which when added together gives a final number. Got that? I know this sounds extremely complicated but in order for me to be confident in the robustness of this methodology it has to be mathematically sound.

  13. Facinating analysis. I think that we have just scratched the surface of the applications of Twiiter and how powerful it can be.

  14. Hello cool index very detailed. is there a way people can put in their own twitter id – or others to see a relative score? for instance – how influencial am i vs others that follow me/or i follow?


  15. As a top Twitter business user, I was sent an advance copy of the Tweet Adder System for my review. This is by far the best Networking Tool I have used for Twitter!

  16. I read that he was to eager do a Coronation Street appearence :O. Sounds a bit dodgy to me. There’s a bit of me that kind of hopes this is true lol.

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