A graphical report on a search for up to 1500 recent tweets tagged #solo12.
First, who is being RTd, and how often were they RTd in the sample?
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Let's start by seeing who's been tweeting most amongst the sampled tweets…
And who's been RTd most:
It's easy to add in Google Chart component sortable tables (click on column header to sort by column):
Start off with some simple summary tables of who's been tweeting, RTd, etc.
| Name | rtofCount | toCount | rtbyCount | fromCount | |
|---|---|---|---|---|---|
| 1 | LouWoodley | 39 | 10 | 12 | 51 |
| 2 | dellybean | 30 | 5 | 6 | 50 |
| 3 | SpotOnLondon | 25 | 5 | 13 | 43 |
| 4 | Protohedgehog | 24 | 1 | 20 | 24 |
| 5 | DrJennyWoods | 24 | 1 | 20 | |
| 6 | grace_baynes | 20 | 1 | 3 | 22 |
| 7 | eperlste | 16 | 6 | 2 | 15 |
| 8 | hapsci | 15 | 4 | 2 | 24 |
| 9 | JennyRohn | 12 | 4 | 4 | |
| 10 | Gurdur | 10 | 5 | 34 |
| Name | rtbyCount | rtofCount | toCount | fromCount | |
|---|---|---|---|---|---|
| 1 | Protohedgehog | 20 | 24 | 1 | 24 |
| 2 | SoapboxScience | 14 | 15 | ||
| 3 | SpotOnLondon | 13 | 25 | 5 | 43 |
| 4 | LouWoodley | 12 | 39 | 10 | 51 |
| 5 | laurawheelers | 11 | 5 | 1 | 30 |
| 6 | AnneOsterrieder | 11 | 3 | 2 | 27 |
| 7 | mattjhodgkinson | 10 | 2 | 1 | 10 |
| 8 | Science_Grrl | 9 | 6 | 1 | 12 |
| 9 | sharmanedit | 8 | 7 | 4 | 19 |
| 10 | clearsci | 8 | 5 | 2 | 17 |
| Name | fromCount | rtbyCount | rtofCount | toCount | |
|---|---|---|---|---|---|
| 1 | LouWoodley | 51 | 12 | 39 | 10 |
| 2 | dellybean | 50 | 6 | 30 | 5 |
| 3 | pssalgado | 46 | 6 | 8 | 2 |
| 4 | SpotOnLondon | 43 | 13 | 25 | 5 |
| 5 | Gurdur | 34 | 10 | 5 | |
| 6 | nailest | 30 | 5 | 9 | |
| 7 | laurawheelers | 30 | 11 | 5 | 1 |
| 8 | AnneOsterrieder | 27 | 11 | 3 | 2 |
| 9 | quelet | 25 | 4 | 1 | |
| 10 | Protohedgehog | 24 | 20 | 24 | 1 |
Now let's try an accession plot (based on an oriiginal idea by @mediaczar)
The accession plot shows the accession of folk using the search term in the tweet sample, and each of their sampled tweets thereafter.
We can add value to the chart by colouring tweets to see which were original tweets and which were RTs.
We can also limit the chart to only show original tweets:
Or only show RTs:
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Let's look to see what tags were used in the sample four times or more:
| tag | tagCount | |
|---|---|---|
| 1 | #solo12 | 1384 |
| 2 | #solo12WIS | 87 |
| 3 | #solo12alt | 65 |
| 4 | #solo12edu | 65 |
| 5 | #SoLo12 | 48 |
| 6 | #SOLO12 | 46 |
| 7 | #solo12sp | 44 |
| 8 | #solo12newmedia | 40 |
| 9 | #solo12SP | 36 |
| 10 | #solo12jobs | 35 |