Weitere ähnliche Inhalte
Ähnlich wie Classifying Twitter Content (20)
Mehr von Stephen Dann (20)
Kürzlich hochgeladen (20)
Classifying Twitter Content
- 1. Classifying Twitter Content Dr Stephen Dann Australian National University @stephendann Presented at Marketing Science, Houston, June 11, 2011
- 2. If you’re on Twitter Questions can be sent to @stephendann or Hashtag #mktsci2011
- 6. How to analyze a living medium? Hawthorn Effect*Uncertainty Principle Sample Size / Twitter Volume [ ]
- 22. 1072 1823 4344 1020 602 2811 11672 Total 31 34 126 153 10 834 1188 10% Status 20 24 69 60 12 213 398 3% Phatic 896 949 2780 351 533 278 5787 50% Pass Along 10 31 784 29 17 13 884 8% News Events 115 785 585 427 30 1473 3415 29% Convers-ational Ener. Counc. Police #Conf #Dis. Dann n Data
- 25. The Challenge Time Day Month Year * Spam gets a category indicated as “Delete” 140 characters of text [C] [S] [PA] [N] [P] [X]* [C 1 ] [C 2 ] [C 3 ] [C 4 ] [S 1 ] [S 2 ] [S 3 ] [S 4 ] [S 5 ] [S 6 ] [S 7 ] [S 7 ] [PA 1 ] [PA 2 ] [PA 3 ] [PA 4 ] [PA 5 ] [N 1 ] [N 2 ] [N 3 ] [N 4 ] [N 5 ] [N 6 ] [N 7 ] [P 1 ] [P 2 ] [P 3 ] [P 4 ] [X 1 ] [X 2 ] [X 3 ] [X 4 ]