Top analyst tweeters (via TweetLevel)

19Jan10

There is little doubt that the growth of Twitter has fundamentally changed the way that conversations, ideas and influence are spreading around the web. Previously the domain of a few in the analyst world, several months ago, there was a noticeable shift in the adoption of Twitter by this community and it was fair to say that it had reached its tipping point.

However, with this growth, AR pros reached a common problem. Should they spend their limited time interacting with analysts via twitter (as well as through all the other channels). The answer was most succinctly answered by Jeremiah Owyang of Altimeter Group in a quote that I like to refer to often:

I’ll be very clear on this. If you want to influence me, be in a conversation and dialog with me, in person, online, and wherever I go.

Consequently it became important to understand which are the analysts that are using this tool well. The concept of tiering is not new, we have been doing this for years to ensure that we spend our increasingly limited time with those people that have the largest influence. The problem however, with many of the tiered lists is that the greatest weight is given to the number of followers  someone has. In my opinion this is fundamentally flawed within AR as it is more important to understand which analysts are most engaged and trusted as oppose to merely popular.

TweetLevel aims to answer this question.

This unique tool compiles twitter data from over 30 sources and feeds the data through an algorithm to rank an individual according to four weightings:

  1. Popularity (i.e. How many people follow you)
  2. Influence (i.e. What you say is interesting, relevant and many people listen)
  3. Engaged (i.e. You actively participate within your community)
  4. Trusted (i.e. People believe what you say)

Of course, the explanation above is a simplified definition of a complex algorithm(the full methodology of this is shown at the bottom of this post).

image

I personally use this list by looking at a micro topic area (such as SaaS) and understand out of the 750+ analysts on Twitter which are the ones that truly use this as a conversation tool. I am normally left with ten names who I now know are critical to engage with.

TweetLevel results for analysts

  1. Kudos to Jeremiah who is not only the top analyst tweeter but also the top analyst blogger. This is an amazing achievement to which I salute you.
  2. The big guns have now taken note of Twitter and are now actively engaging in conversations. Who’d have thought that when I first compiled this list Gartner presence was poor.
  3. Small firms are far more visible using Twitter. Hat tip again to the RedMonk (and GreenMonk) crew for having a voice that reaches the masses.
  4. Analysts that use Twitter don’t only specialise in social media (although those that appear near the top of this list tend to work in this space).
  5. Details of over 750 analysts were put through the TweetLevel algorithm (names largely taken from the amazing directory at SageCircle). A big change to when I first calculated this

 

    Account Influence Popularity Engagement Trust
1 jowyang 73.1 71.1 52.7 75.9
2 Econsultancy 63.6 63.1 41.4 71.8
3 forrester 62.7 67.5 45.5 63.7
4 rwang0 60.8 55.7 43.3 55
5 monkchips 60.1 58.1 49.6 56.3
6 TomRaftery 56.4 56.8 51.5 55.5
7 hharteveldt 55.6 51.4 50.1 51.5
8 Gartner_inc 55.4 64.5 38.1 57.9
9 ekolsky 55.3 46.6 58.8 49.2
10 gyehuda 54.7 50.6 52.1 47.6
11 charleneli 54.6 66.5 52.5 47
12 drnatalie 54.3 56 42.8 46.7
13 richi 54.2 54.6 60.7 46.5
14 cote 54 52.9 47.7 46.1
15 jyarmis 54 50.9 55 45.8
16 augieray 53.6 53 47.6 45.9
17 jbernoff 53.2 58.8 56.4 45.7
18 rshevlin 52.5 44 65.9 42.8
19 mfauscette 52.3 56.7 37 44.1
20 merv 52.2 48.2 56.5 41.2
21 storageio 51.9 46 57.1 41
22 sogrady 51.7 49.1 47.7 41.4
23 rmogull 51.7 48.6 56.6 38.4
24 vendorprisey 51.4 47.5 54.8 39.1
25 denschaal 51.3 49.7 49.3 42.8
26 VanessaAlvarez1 50.8 48.1 49.3 47.2
27 cuttertweets 49.9 45.7 37.4 44.6
28 jclarey 49.8 52.2 47.1 37.3
29 Hitwise_UK 49.8 58 45.7 48.3
30 kasthomas 49.7 61.2 37.1 44
31 nselby 49.7 44.3 53.8 39.9
32 debs 49.6 56.3 54.7 37.3
33 stephenodonnell 49.6 49.5 48.1 41.9
34 john_chilmark 49.5 48.4 42.1 39.7
35 Gartenberg 49.5 55.2 48.8 44.9
36 jameskobielus 49.4 47 37.5 39.5
37 bmichelson 49.2 47.2 48.2 38.1
38 carterlusher 49.1 50.9 42.4 38.7
39 bkwalker 48.7 48.3 36.5 39.4
40 vtri 48.7 45.3 45.5 39.3
41 blairplez 48.6 45.4 46.9 39.6
42 Enderle 48.5 57.2 41.6 48
43 samirb 48 48.4 51.8 36.3
44 steven_noble 47.9 49 48.2 36.2
45 bobegan 47.6 44.7 48 38.8
46 Hitwise_US 47.4 58.5 39.5 47.3
47 NeilRaden 47.3 45.6 59.5 39
48 lehawes 47.1 45 52.9 31.1
49 CurtMonash 47 51 43.8 40.6
50 AndiMann 47 46.9 44.6 43.8
51 dealarchitect 46.8 43.3 58.7 37.9
52 robinbloor 46.7 55.6 9 38.2
53 gilliatt 46.6 48.7 49 32.2
54 nate_elliott 46.6 50.6 42.8 33.3
55 JimLundy 46.3 46.7 53.5 39.8
56 InFullBloomUS 46.3 48.1 41.3 42
57 stiennon 46.1 63.4 49.7 28.5
58 jonno 46 45.9 54.5 30.5
59 Claudia_Imhoff 46 47.1 54.9 40.1
60 SethGrimes 45.9 47.6 59.2 40.7
61 idarose 45.8 49.3 43.4 30.8
62 PhoCusWright 45.6 50.6 33.4 41.8
63 Mark_Mulligan 45.6 50.7 48.6 38.8
64 dvellante 45.4 43.1 58.9 30.1
65 s_crawford 45.2 44.6 46.3 33.3
66 arj 45.1 44.8 52.5 33.9
67 lauraramos 45.1 50.6 29.9 40.8
68 mark_koenig 45.1 40.7 46.8 38.9
69 ghaff 44.9 42.3 46.3 36.1
70 dankeldsen 44.7 54.9 45.9 26.6
71 bitterer 44.6 46.7 50.3 26.9
72 megheuer 44.4 48.4 41.3 33.2
73 jamet123 44.4 45.1 32.7 35.8
74 jonathaneunice 44.3 46.8 49.2 28.1
75 jhurwitz 44.1 50.8 40.6 33.5
76 dale_vile 43.9 44.5 57.4 29.8
77 stevedupe 43.8 46.2 32.9 38
78 clivel_98 43.7 43 54.2 29.4
79 JEBworks 43.7 47.7 47.4 35.6
80 cmswatch 43.6 52 36 41.4
81 stephenmann 43.6 44 45.9 31.1
82 caostheory 43.6 42.3 0 42.8
83 EricaDriver 43.5 45 40.1 38.3
84 Dana_Gardner 43.5 49.8 32 41
85 krestivo 43.5 46.5 48.6 27.7
86 Jake_Hird 43.4 43.9 40.1 38.6
87 mgualtieri 43.4 45.4 37.8 35.9
88 cmendler 43.3 44.2 45.1 34.1
89 abnerg 43.1 47 44 29.3
90 fscavo 42.9 45.9 5.7 33.8
91 rgruia 42.9 47.2 48.1 24.4
92 janovum 42.8 40 54.3 30.5
93 fiberguy 42.8 40.6 43.4 31.9
94 the451group 42.7 50 23.6 37.4
95 atmanes 42.7 44.9 39.7 29
96 gilbane 42.7 48.7 34.5 37.8
97 michaelwolf 42.7 41.3 40.7 33.5
98 btudor 42.3 42.5 46 32.1
99 jblock 42.2 53.6 34.3 28.5
100 biz_mobility 42.2 41.4 44.8 31.8
101 KarenYetter 41.9 59.8 10 34.7
102 Thomas_Husson 41.9 44.4 34.8 41.4
103 markmadsen 41.8 45 49.6 22.5
104 pragkirk 41.7 43.9 38.4 35
105 seuj 41.5 34.5 53.9 27.4
106 maslett 41.5 40.1 35.9 33.1
107 antallan 41.5 42 46.5 24.9
108 znh 41.5 45.8 37.8 26.7
109 stylishidea 41.3 46.7 36.5 22.2
110 jimholincheck 41.3 44.6 35.4 35.5
111 johnrrymer 41.2 45.8 37 34.7
112 adamhleach 41.2 39.5 47.3 27.9
113 802dotchris 41.1 42.7 44.7 35.7
114 gwoodill 41 50.6 42.9 31.3
115 martinatherton 41 40.7 45.7 28.2
116 SteffWatson 40.8 36.2 37.5 36.1
117 dschatsky 40.7 43.5 31.6 30.8
118 dnm54 40.7 38.4 33 30.4
119 infotrends 40.6 45.4 32.2 34.7
120 JeffreyBreen 40.6 44.4 39.5 32
121 sureshvittal 40.3 45.4 37.2 35.1
122 storageswiss 40.2 43.9 32.1 34.8
123 mosterman 40.1 41.2 7.7 33.6
124 stessacohen 40.1 41.9 39.3 34.1
125 bradholtz 39.9 42.8 34.5 29.5
126 Montejam 39.9 42.7 40.3 31.9
127 IDC 39.9 55.1 4.7 41.1
128 Douglas_Quinby 39.8 44 42.4 33.6
129 TonyBaer 39.8 40.1 52.3 31.9
130 Staten7 39.8 42.8 33.7 37.2
131 pattyinboothbay 39.7 47 30.1 27.8
132 timehhh 39.7 41.3 40.5 25.2
133 lisarowan 39.7 44.2 33.2 30.9
134 brian_riggs 39.6 41.6 31.8 33.9
135 neilwd 39.5 41.6 40.4 27.6
136 AndreaDiMaio 39.4 44.1 5 38.7
137 tomcummings 39.2 48.7 49.8 20.9
138 rayval 39.2 48.1 35.8 28.1
139 bfinucane 39.1 46.9 48.6 24.7
140 paulhamerman 39.1 41.4 27.7 34
141 rossrubin 39.1 46.8 45.6 21.3
142 cswolf 39.1 45.1 46.5 21.5
143 IDCInsights 39.1 49.8 35.8 32.8
144 iglazer 39 42.7 45.4 22.5
145 jeffmann 38.8 46.4 37.8 22.4
146 Wikibon 38.8 43.3 29.6 33
147 andreascon 38.6 43.3 32 34.1
148 billtrippe 38.5 46.6 37.2 22.1
149 johnlovett 38.1 45.5 43.8 29.6
150 NickLippis 38 44 29.9 31.3
151 PhilippBohn 38 42.2 40.9 31.3
152 vgtero 37.7 44 33.8 21.5
153 darranclem 37.6 41.6 37.9 23.3
154 jhammond 37.6 43.6 33.7 23.8
155 siriusdecisions 37.4 45.2 35.5 30.6
156 smulpuru 37.4 46.1 26.2 30.4
157 btemkin 37.3 44.5 0.7 36.4
158 esganalysttmac 37.3 42.1 42.1 33.8
159 erainge 37.3 42.6 31.6 31.4
160 adriaanbloem 37.3 39.6 49.8 22
161 ema_research 37.2 44.5 6.3 35
162 sliewehr 37.2 36.5 41.4 32.7
163 FreeformCentral 37 42.9 36.4 37.5
164 jalvear 36.9 41.4 40.4 21
165 bryanyeager 36.8 37.8 34.4 28.8
166 MaribelLopez 36.8 45.6 44.4 23.3
167 iSuppli 36.7 44.5 5 32.3
168 aschmitt 36.7 37 34.3 25.7
169 randygiusto 36.4 44 33.6 22.8
170 mbrandenburg 36.3 40.8 40.2 24.7
171 allenweiner 36.2 45.5 30.7 19.3
172 ianfogg42 36.2 42.7 32.8 21
173 omriduek 35.9 39.7 36.3 22.2
174 davidcard 35.8 45.8 29 23.1
175 keith_rng 35.6 43.7 7.7 20.4
176 paulfroberts 35.5 43.5 33 24.1
177 JeffPR 35.5 45.6 36.4 25.5
178 rogermud 35.3 41.6 28.3 23.5
179 StefanRied 35.3 42.8 26.5 28.5
180 rnantel 35.2 39.7 28.2 25.3
181 glennodonnell 35.2 42.3 44.8 21.3
182 SarahBurnett 35.1 46.1 42.6 21
183 jim_techclarity 35.1 39.7 40.6 25.5
184 RayLucchesi 35.1 41.8 55.7 27.1
185 Mark_Goldberg 35.1 37.8 30.7 31
186 YankeeGroup 35.1 47.5 5 31
187 Lciarlone 35.1 42.8 38.1 24.9
188 joeltweet 35.1 60 41.3 21.7
189 etravelproject 34.8 46.2 33.6 19
190 dkusnetzky 34.8 41 43.3 24.2
191 ravenzachary 34.7 46.2 29.6 19.1
192 toppundit 34.7 42 5 31.5
193 tebbo 34.7 43.7 5 20.2
194 npdgroup 34.6 48.6 4 35.3
195 timbo2002 34.6 43.7 34.4 18.8
196 Gabeuk 34.3 41.3 42.6 23.3
197 rreitsma 34.3 39.8 29.8 32.3
198 lauriemccabe 34.2 39 30.5 26.8
199 Zak_Kirchner 34 41.3 7 23.8
200 demartek 33.9 42.3 32.1 22.6
201 EquaTerra 33.9 42.3 6.3 36.2
202 Payment_Expert 33.9 48.8 29.2 34
203 TomGrantForr 33.9 41.9 25.4 27.4
204 BarryRabkin 33.8 43.3 41.7 21.8
205 gleganza 33.8 42.2 45.9 18.6
206 nickpatience 33.7 38.7 33.4 28.4
207 hyounpark_AG 33.6 42.5 29.8 27.8
208 jpmorgenthal 33.6 44 33.7 18.6
209 Heuristocrat 33.4 44 29.6 20.8
210 bevelson 33.3 38.6 34.4 26.9
211 TKspeaks 33.3 55.4 35.1 30.2
212 LockTD 33.3 39.8 39.8 19.6
213 bmirabito 33.2 50.4 30.6 19.2
214 thinkovation 33.1 42 40.5 18.6
215 BurtonGroupIT 33.1 46 6.3 28
216 pfersht 32.9 45.1 45.3 21.6
217 gilbaneboston 32.9 50.5 33 19.2
218 punirajah 32.8 37.6 32.6 19.2
219 TonyByrne 32.8 46.1 36.8 25
220 msbrumfield 32.7 42.6 26.3 19.7
221 Bersin 32.7 52 27.7 32.4
222 LinusGreg 32.7 46.1 33.5 23
223 ekmurphy 32.7 38.3 36 19.2
224 MarkRaskino 32.7 42 29.5 24.4
225 pjtec 32.6 34.2 28.6 26.9
226 dxmitche 32.6 45.4 34.3 18.6
227 imlazar 32.5 41.9 39.4 19.6
228 rschmelzer 32.5 41.2 32.9 19.4
229 Frost_Sullivan 32.4 42.2 5 25.5
230 visionmobile 32.2 41.9 25.7 28.2
231 markbowker 32.1 40.5 25.2 31.6
232 MattRosoff 32.1 44.6 29.8 25.1
233 ironick 32 38.5 36.2 19.1
234 CurrentAnalysis 31.9 44.3 0.3 28
235 pund_it 31.7 37 33 18.9
236 adamjura 31.6 38.8 40.8 19.8
237 mlevitt 31.6 44.1 23.9 17.6
238 jblin 31.3 39.5 26.4 16.7
239 shigginski 31.3 36.9 29.2 16.9
240 bsdunlap 31.2 40.9 28.7 17.4
241 scottn7 31.2 40.1 24.1 17.1
242 dfrankland 31.2 44 30.1 22.9
243 katiesmillie 31.1 40.7 31.4 18.9
244 Jossgillet 31.1 33.5 36.7 20.4
245 TheNakedChief 30.9 35.3 25.5 24.2
246 gilbanesf 30.8 42.1 30.3 24.1
247 lightplay 30.8 33.2 36.3 25.2
248 NPDFrazier 30.8 41.8 37.7 29.1
249 tjkeitt 30.8 37.9 34.9 19.4
250 ca_bshimmin 30.7 43.2 28.5 18.9
251 iangjacobs 30.7 42.5 31.1 17.5
252 nora_freedman 30.7 43.4 42.6 17.7
253 SeanCor 30.7 47.5 36.3 24.5
254 jmcquivey 30.6 43.7 39 18.8
255 nyuhanna 30.6 48.6 28.6 18.5
256 cee_m_bee 30.6 41.3 33.5 17.4
257 alyswoodward 30.5 38.2 44.6 16.9
258 pmcginnis 30.5 42.9 32 17.1
259 Gartnergreg 30.5 41.2 31.3 18.5
260 jonathanbrowne 30.3 44.1 33.3 17.3
261 epopova 30.3 38 24.4 23.4
262 cmooreforrester 30.3 42.9 26.7 20.5
263 theresaregli 30.3 43.2 34.6 19.5
264 Celent_Research 30.2 43.2 27.3 25.5
265 passingnotes 30.2 42.1 37 17.3
266 passion4process 30 41.7 27.6 18.9
267 erichknipp 30 38.6 5.3 19.5
268 analystnick 29.7 40.8 33.7 17.2
269 rbkarel 29.6 38.7 32 21.1
270 mbkmbk 29.6 38.6 28.3 20.2
271 katehanaghan 29.5 40.5 39.2 17.1
272 dmavrakis 29.4 37.8 35.6 16.5
273 jjegher 29.3 42 34.9 17.5
274 brucemr 29.3 35.1 28.9 15.6
275 NewsShark 29.3 44.3 24.8 21.1
276 mlees 29.2 39.1 25.2 19.2
277 royillsley 29.2 42 26.6 16.7
278 euroLAN 29.2 39.4 30.3 25.8
279 AlanWebber 29.1 44.7 32.5 18.5
280 nengelbert 29 42.4 28.2 16.6
281 nickster2407 29 39.9 33.5 16.5
282 Neovise 28.9 37.2 28.3 21.6
283 jcapachin 28.9 38.7 27.8 19.5
284 minicooper 28.9 45 34.9 17.4
285 chris_townsend_ 28.9 42.5 40.5 17.3
286 rob_bamforth 28.8 36.7 29.8 16
287 SA_Update 28.8 39.3 3 29.1
288 ripcitylyman 28.7 38.6 6.7 17.1
289 DenisPombriant 28.7 42.7 26.8 23.5
290 ventanaresearch 28.6 43.5 26.9 17.8
291 howett 28.6 32 34.5 15.5
292 heyshiv 28.5 35 46.6 16.3
293 joltsik 28.5 40.2 19.6 29.1
294 GaryatWikibon 28.5 39.4 29.7 16.9
295 TECtweets 28.5 37.2 25.8 25
296 KeithHumphreys 28.5 44.2 34.3 19.3
297 vvittore 28.3 34.8 29.5 17.2
298 mcgeesmith 28.3 37.4 31.5 21.3
299 billnagel 28.2 34.3 32.3 15.7
300 VLI 28.2 35.8 36.7 16.2
301 Hitwise_AP 28.1 50.9 8.7 21.8
302 mgrey 28 39.4 3.7 17.6
303 gcolony 28 56.9 22.6 19.3
304 AgingTech 27.9 41.6 27.4 24.2
305 jensbutler 27.9 36.3 29.2 16
306 ferrusi 27.9 36.6 30.1 15.6
307 darrenbibby 27.8 39.4 23.2 17.6
308 cdhowe 27.8 34.5 26.2 21.3
309 tim_walters 27.7 40.1 30.1 18.2
310 stor2 27.7 40.3 23.2 15.5
311 DaveMario 27.6 38.2 31.9 20.3
312 infotrends_mps 27.6 37.9 30.7 15.4
313 kreidy 27.4 41.1 39.2 18.1
314 azornes 27.3 38 4.3 15.5
315 PHassey 27.3 35.5 32.4 16.2
316 REdwards 27.2 41.1 22.5 20.7
317 JoeGalvin 27.1 37.4 25.5 25.1
318 CRozwell 27 41.3 31.1 19
319 jeunice 27 38.2 29 15.7
320 iTGuru 26.8 38.6 24.3 25.6
321 algillen 26.8 35.6 27.1 20.8
322 PaulBrown_SA 26.8 36 29.5 20.8
323 NormTravelTech 26.8 42.5 31.6 20.4
324 reastman 26.8 39.6 28.5 15.6
325 diteb 26.7 41.9 33.4 16
326 acfrank 26.7 41.2 24.7 15.5
327 melanieturek 26.7 38.1 31.7 15.8
328 richwatson 26.7 40.2 28.7 19.6
329 benwood 26.7 43.1 25.7 19.6
330 KeithKTsang 26.7 39.3 30.9 17.2
331 sjschuchartCA 26.6 38.9 46 16.9
332 fjeronimo 26.6 36.5 25 15.1
333 lcecere 26.5 41.1 27.9 16
334 ForresterJobs 26.4 49.4 32.4 18.4
335 heidishey 26.4 36.8 33.8 15.2
336 jfrey80 26.3 40.8 22.9 19.3
337 alexkwiatkowski 26.3 39.7 27.4 15.7
338 smwat 26.3 33.6 22.8 16.1
339 Rick345 26.3 40.1 25.8 18.1
340 jaysonsaba 26.2 41.5 27.8 16
341 nigelwallis 26.2 32.5 36.3 14.5
342 bseitz 26.2 31.5 36.4 14.1
343 idccanada 26.1 44.9 7.7 15.8
344 ARC_Advisory 26.1 43.7 24.8 16.8
345 whita 26.1 36.9 39.7 15.4
346 zmcgeary 26 43.2 39.3 16.1
347 hokun 25.9 39.5 33.5 15.8
348 Horses4Sources 25.9 41.6 25.5 23.4
349 carldoty 25.9 38.6 25.4 15.2
350 zkerravala 25.9 38.6 21.1 15.3
351 ChristianKane 25.8 39.3 32.7 16.3
352 D_Hong 25.7 42.6 6.3 16.1
353 strothkamp 25.7 35.9 24.8 21.9
354 stavvmc 25.7 32.6 33 16
355 DaveBoulanger 25.6 46.8 51.7 17.8
356 Teresacottam 25.6 38.8 26.7 23.2
357 fgilbane 25.5 41.3 31.6 15.6
358 securityjeff 25.5 37 38.9 15.2
359 smcleish 25.5 37.8 28.6 18.7
360 mtauschek 25.4 33.6 30.3 14.5
361 diane_clarkson 25.4 41.8 22.7 19.2
362 TGView 25.4 36.5 26.8 15.3
363 Shawn_McCarthy 25.4 37.9 30.9 15.7
364 fgens 25.3 42.3 26.2 17.6
365 drjimmys 25.3 35.9 20.7 14.1
366 thickernell 25.3 36 22.3 14.7
367 markpmcdonald 25.3 38.6 4 16.7
368 TechMarketView 25.3 35.4 21.5 18.3
369 susankevorkian 25.2 37.6 20 16.4
370 annenielsen 25.2 40.7 23.9 15.2
371 mobilesimmo 25.2 37.1 24.5 14.8
372 Nemertes 25.1 39.3 6.7 18.7
373 Burgess_Gary 25 34.9 29.6 17
374 mHingley 25 40.1 5.3 19.4
375 Andrew_Boyd 25 46.4 31.8 16.9
376 dlevitas 24.9 38.2 26.5 14.7
377 dpotterton 24.9 35.2 18.7 15.8
378 Josh_Bersin 24.8 52.9 24.6 18
379 markhrobinson 24.8 41.3 24.3 15.8
380 andreasantonop 24.8 39.4 36.1 14.9
381 Aberdeen_CMTG 24.7 49.4 25.3 17.4
382 hkisker 24.6 35.3 21.7 14.2
383 PeteCunningham 24.6 39.5 33.9 16.9
384 jonarber 24.6 35.4 29.3 15.1
385 chrischute 24.6 31.8 28.6 15.4
386 DouglasHayward 24.6 33.2 25.2 19.9
387 AMR_Research 24.6 52.3 24.2 17.9
388 debswee 24.5 34.2 29.5 14.1
389 jeffkagan 24.5 47.1 21.6 17.6
390 rwhiteley0 24.5 40.3 28.5 15.2
391 tonyiams 24.4 31 22.2 18.8
392 FillMurphy 24.4 34.1 25.4 20.2
393 richardwinter 24.4 36.6 44.7 14.5
394 jamystewart 24.3 41 22.1 16.7
395 brightfly 24.3 40.7 5 14.8
396 mgilpin 24.3 38.4 30.9 15.2
397 jonathansteel 24.3 40.6 26.7 15.3
398 Craw 24.2 41 28.4 18.1
399 waband 24.2 41.7 24.6 17.7
400 nsturgill 24.1 34.3 20.6 15.7
401 100Gigabit 24.1 44.1 24.4 16.1
402 MattyHatton 24.1 40.7 33 16.1
403 jctec 24 30.4 21.6 18.1
404 Senformation 23.9 37.8 33.7 15.3
405 instantBP 23.9 39.4 26.7 15.5
406 jamesbrehm 23.8 36.6 21.5 15.8
407 jmp_katz 23.7 39.5 28.2 14.8
408 kevinnolanuk 23.7 40.3 23.4 14.4
409 ajbowles 23.7 39.5 21 14.6
410 rsilvalondon 23.7 31.9 2 13.3
411 Madtarquin 23.6 42.1 33.9 16
412 itstorage 23.6 40.7 33.9 15.3
413 SW_Support 23.5 32.2 27.3 24.6
414 philkendall 23.5 37.1 23.9 13.9
415 jamiemlewis 23.5 40.4 30.6 15
416 CompassIntel 23.5 41.3 21.4 15.4
417 tarzey 23.4 38 39.7 14.7
418 MWDAdvisors 23.4 34.3 22.9 21.2
419 lauradidio 23.4 37 4.3 13.8
420 michaelgreene 23.3 37.7 25.7 14.5
421 wkernochan 23.3 31 46.4 13.7
422 OvumICT 23.3 35.4 3.7 21.5
423 wmcneill 23.3 40.2 20.6 14.6
424 instat 23.3 40.3 19.2 14.8
425 infonetics 23.2 43.5 5.3 14.9
426 fab_biscotti 23.2 39.1 25.7 14.3
427 emmaking_escp 23.1 39.4 30.2 14.8
428 geoffblaber 23.1 39.8 28.1 14.7
429 barryparr 23.1 41.9 24.6 15.1
430 mbarbagallo 23.1 39.7 27.5 14.7
431 lisabradner 23 42.5 23.7 15
432 wjmalik 23 34.1 33 13.8
433 chinamartens451 22.9 32.4 21.1 12.9
434 Canalys 22.9 40.5 4.7 15.4
435 dconnor 22.9 40.1 21.2 14.3
436 dtwing 22.9 38 21.8 16.1
437 rkoplowitz 22.9 39.3 26.2 14.8
438 msmvnj 22.9 37.5 23.9 14.1
439 christinaylee 22.8 34.3 32.6 13.7
440 red_gillen 22.7 30.3 19.2 17.9
441 jarrodgingras 22.7 43.3 28.6 15.5
442 jeffheynen 22.6 36.7 24.2 14
443 adriandrury 22.6 31.2 22.9 12.7
444 angie_p 22.6 35.7 31 13.8
445 Nathan_Safran 22.6 36.1 32.1 14.5
446 danolds 22.5 33.4 18.2 13.4
447 NinaLytton 22.5 33.6 28.8 13.9
448 galvar60 22.5 35.9 4.3 13.3
449 Telesperience 22.5 39 19.5 16.7
450 Hils_of_IT 22.4 38.5 30.3 14.8
451 carriejohnson 22.4 38.6 27.2 14.4
452 srepps 22.4 39.7 29.6 14.6
453 pdebeasi 22.4 40.5 19.2 19
454 MobileAberdeen 22.3 42.1 26.1 15.6
455 srog 22.3 40.9 41.8 15.1
456 CCSInsight 22.3 40.7 21.1 18.8
457 tombitt 22.3 40 34.1 14.8
458 miravperry 22.3 37.8 26.2 13.9
459 wif 22.2 37.1 25 14.8
460 wfz 22.2 33.5 5 12.6
461 bswtelecom 22.2 39.1 19.3 16
462 elizabethstark 22.2 35.5 27.9 13.6
463 dkerrsa 22.1 30.2 20.2 16
464 TheTowerGroup 22.1 35.8 23.5 18.2
465 gphifer 22.1 41.1 4.3 14.3
466 tjennings 22 39.6 25.1 14.3
467 RichBohn 22 46.1 8.3 15.4
468 MKRasmussen 22 42.2 4.7 18.7
469 dougwashburn 22 38.2 26.7 14.1
470 bgassman 21.9 40.1 27.1 14.7
471 wzhou 21.9 35 22.2 13.3
472 dreeves1 21.9 29 32 12.5
473 jackzimmerman 21.8 38.1 17.5 13.9
474 TedSchadler 21.8 41.9 18.8 19.2
475 vernonxt 21.8 36.9 19 13.7
476 tcorbo 21.7 38.4 24.1 13.9
477 mgerush 21.7 38.4 22.6 13.8
478 cborovick 21.7 37.4 22.8 13.6
479 zapthink 21.7 32.2 14.9 13.1
480 angela_ashenden 21.7 30.8 19.8 16.1
481 pete_lacey 21.7 30.8 21.6 12.4
482 adelesage 21.6 36.6 27.1 15.4
483 davidmsmith 21.6 39.7 21.7 14.2
484 LFrankKenney 21.6 35.7 28.7 14.5
485 shauncollins 21.6 39.3 20.5 14
486 ABI_4G 21.5 34.3 19.7 15.3
487 davecapp 21.5 34.9 24.7 13.3
488 sebastiancoss 21.5 36.7 19.1 13.4
489 marksdriver 21.5 37.6 3 13.5
490 CushingAnderson 21.4 39.5 30.2 14.7
491 scottsantucci 21.4 37.1 20.2 13.4
492 tim_shepherd 21.4 40.3 14.7 14.1
493 140letters1idea 21.4 32.7 22.1 12.7
494 julie_craig 21.4 31.8 18.4 12.8
495 ChrisOber 21.3 35.3 23 14
496 monkchipsconf 21.3 32.6 23.2 12.8
497 DortchOnIT 21.3 40.3 27.9 15.1
498 DavidJWest 21.3 36.3 3 20.9
499 ITAnalysis 21.3 30.5 4.3 14.2
500 benwoony 21.2 36.5 20.7 13.5

Algorithm and Methodology

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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. Note: Twitter opened its API to TweetLevel so that data could be sourced easily and quickly to benefit the user.

Followers – Twitter lists the number of people that follow each user. Like subscribing to a feed, this is a clear indication of ‘popularity’ as it requires someone to actively request participation. Even though TweetLevel has a ranking of people based upon popularity, it is influence, engagement and trust that is more important. Due to the nature of logarithmic ranges, a change in the number of people that follow someone, such as from 500 – 1000, will give a far higher change in score than a move from 180K – 200K. 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. Note: Twitter opened its API to TweetLevel so that data could be sourced easily and quickly to benefit the user.</p>

Twitter Lists – without a doubt this feature addition to Twitter will significantly change the influence score. Even though Twitter has released their API to us, this particular metric is not yet included. When it is, a TweetLevel score will increase depending upon the number of times a user is included in a list, the number of people who follow that list and the authority of those people.

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 – The Involvement Index is unique Edelman IP that calculates a score based upon how an individual engages with their community. It is calculated by analysing the content of an individual posts. People who score highest in this category have 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.

Weighted for trust – the best measure of trust is whether an in individual is will to ‘trust’ what someone else has said sufficiently that they are also prepared to have what they tweeted associated with them. The key metric in this instance are a combination of retweets and number of followers. Other attributes were included in the final score but were given a lower weighting.

In the true spirit of ‘open sourcing’ this work, I welcome your comments, views and criticisms in how this approach can be as accurate as possible. Whereas I don’t believe for one moment that TweetLevel has found the holy grail of social media measurement, I think it is a good step forward and look forward to discussing this with you.

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41 Responses to “Top analyst tweeters (via TweetLevel)”

  1. Jonny thanks for all you do for the industry, you’re a real asset to Edelman and the space. It’s great to learn from what others are doing. Keep up the great work

    #SalutesBack

  2. Thanks Jonny, we now feel especially influential, but not quite as influential as the mighty Jeremiah!

  3. Jonny,

    What Jeremiah said – this is a superb resource which was obviously non-trivial to produce – kudos to you and many thanks for this.

  4. Thanks of including me.

    Is the influence score black on dark blue background an attempt to obscure things from older analysts like me ;-)

  5. Love it. Great analysis.

  6. Jonny,

    Thanks for the inclusion. Much appreciated. Keep on keeping on!

    -Sam.

  7. Please add me to your analysis next time. I would have been #27 on this list with an Influence Score of 50.

    Jim Berkowitz
    CRM Mastery, Inc.

    http://www.twitter.com/jberkowitz

    Thanks so much.

  8. Hi there Jonny,

    Thanks for including me as well. As number 164, it gives me great incentive to reach number 1 next time!

    Seriously, this is a great, fascinating service. As an independent analyst, it’s much harder to have that involvement with clients, since I’m not the main client contact.

    Twitter still isn’t being used by the analyst community much. There’s definitely an opportunity here.

    Enjoy,

    Jose

  9. Many thanks for including me, especially since I’ve been pretty quiet in the Twitterverse as I recover from shoulder surgery. Much more coming as I regain use of my left hand on the keyboard.

  10. Hi Johnny,

    Thanks so much for this. As #162, I’m honored just to be included with the very well-respected individuals on this list. Thanks so much for this service, it’s obviously quite a feat to produce.

    All the best,
    Scott
    @sliewehr

  11. A great list and congratulations to all the fine analyst-tweeters who are represented here!

  12. 12 Esteban Kolsky

    Jonny,

    Thanks for including me and for the work you did on this. Very interesting.

  13. Thanks for sharing this with us. I just created a Twitter list of the top 50 analysts ranked here. If you find this topic interesting, you should definitely follow it:

    http://twitter.com/SeanWF/top-analyst-tweeters

  14. Great list!

    We would like to have been on it, though. J. Boye regularly tweets about market trends, vendors and customer experiences. You can find us here: twitter.com/jboye

    Hope to join the gurus in version 2 :-)

  15. Johhny, this is an outstanding idea, thanks for sharing. Could we borrow some of your thinking to create a UK focussed list?

  16. Jonny, this is a great idea, thanks for sharing. Could we borrow some of your thinking to create a UK focussed list?

  17. Congratulations to everyone represented here! It is great to be included on a list that was generated using a clear, well-documented methodology The rank to which I was assigned (#48) has much more meaning as a result. Thank you for taking the time to generate this list, Jonny. I hope others will find it useful.

  18. Interesting metrics. Of course, quantitative metrics are for analysts who tweet by the numbers. I tweet to clarify my own thinking, and secondarily to publish it (for various reasons). Numbers don’t move me to tweet or do anything else.

  19. 19 durakje

    This is hilarious. I score in the top half, several places above my CEO, and mine is a personal Twitter account that I don’t use for professional purposes — when I bother to tweet at all.

  20. Thanks Johnny

    I love a good league table.

    BTW new blog is now: http://marcduke.wordpress.com/

    Marc

  21. Thank you for making compiling this important list of analysts. Does this list exist on Twitter or TweepML? Would be extremely useful to follow everyone with one click of a button.

    Thanks,
    Judith

  22. great methodology! You should make “Analyst Tweeters” a category just like you did for “Analyst Blogs” but have both automatically update weekly. These scores change constantly depending on the activity in the blogosphere and Twitterverse each week.

    There were rapid swings for my scores between Jan 19 (this post), your post on analyst blogs, and today.

    But great idea to create a real-time gauge for AR and PR.

    Randy

  23. This is indeed a great and interesting research effort. I’m hoping it will help to make for both smarter and more effective analyst-AR/PR communications AND help users to connect with analysts who can help them make better IT decisions. (I have to admit that it’s also pretty gratifying to be in such illustrious company, especially given that social media is often portrayed as somehow beyond MOACAs (men of a certain age) such as myself! :-)


  1. 1 Quantifications or Qualifications on the Top Analyst Twitter List. | Gil Yehuda's Enterprise 2.0 Blog
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