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bellecarrell
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twitter_brand
In developing a brand on Twitter (and social media in general), how does what you say and how you say it correspond to positive results (more followers, for example)?
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2/10 agenda
#129
bellecarrell
opened
4 years ago
0
Read recommended references
#128
abenton
opened
4 years ago
1
Prepare dataset for public
#127
abenton
opened
4 years ago
2
dynamic model fitting + plotting
#126
abenton
closed
5 years ago
0
5/16 notes
#125
bellecarrell
closed
4 years ago
1
Train dynamic models, collect results
#124
abenton
opened
5 years ago
0
get extracted feature stats
#123
abenton
closed
5 years ago
0
05/13 agenda
#122
bellecarrell
closed
4 years ago
0
Notes about distribution of features in strategy evaluation table
#121
abenton
opened
5 years ago
2
5/9 agenda
#120
bellecarrell
closed
4 years ago
0
extract dynamic feature table
#119
abenton
closed
5 years ago
1
Abenton/extract dynamic features
#118
bellecarrell
closed
5 years ago
0
5/6 agenda
#117
bellecarrell
closed
4 years ago
1
first pass to fit models to test strategy hypotheses
#116
abenton
closed
5 years ago
0
5/2 agenda
#115
bellecarrell
closed
4 years ago
3
4/25 agenda
#114
bellecarrell
closed
4 years ago
0
Add IV types to feature table
#113
bellecarrell
opened
5 years ago
3
Debug generating feature table
#112
abenton
closed
5 years ago
1
4/22 agenda
#111
bellecarrell
closed
4 years ago
1
More NLP-related ideas for these data
#110
abenton
opened
5 years ago
1
4/18 agenda
#109
bellecarrell
closed
4 years ago
2
topic and sentiment extraction
#108
abenton
closed
5 years ago
0
Extract topic and sentiment features per tweet
#107
abenton
closed
5 years ago
3
Build table for fitting regression models
#106
abenton
opened
5 years ago
4
attach a citation to an article and snippet to support hypotheses
#105
bellecarrell
opened
5 years ago
0
statsmodels feature significance
#104
bellecarrell
opened
5 years ago
1
other next steps 4.5
#103
bellecarrell
opened
5 years ago
0
feature list for adrian
#102
bellecarrell
opened
5 years ago
10
Collect together notes for next steps we had talked about, along with reviewer comments
#101
bellecarrell
closed
5 years ago
0
investigate libraries adrian mentioned
#100
bellecarrell
opened
5 years ago
0
2/27/19
#99
bellecarrell
closed
4 years ago
4
extra experiments/thoughts
#98
bellecarrell
opened
5 years ago
0
drop urls, users, and non-alpha strings
#97
bellecarrell
closed
5 years ago
0
Vectorize tweets and write batches to file
#96
abenton
closed
5 years ago
0
implemented ensemble prediction and evaluation
#95
abenton
closed
5 years ago
0
salient features -- main specialization
#94
bellecarrell
closed
5 years ago
1
salient features -- Stability selection on predicting % follower count change: overall, stratified by specialization, and predicting cross-product of labels
#93
bellecarrell
closed
5 years ago
0
salient features -- Stability selection on predicting over cross-product of labels for follower count and specialization
#92
bellecarrell
closed
5 years ago
0
salient features -- Stability selection on predicting follower count across all specializations.
#91
bellecarrell
closed
5 years ago
0
feature selection predicting follower count across all specializations. (updated -- 2 classes, <0.7, >0.9 as low and high)
#90
bellecarrell
closed
5 years ago
0
train dev test split
#89
bellecarrell
closed
5 years ago
3
weekend tasks before abstract deadline
#88
bellecarrell
closed
5 years ago
0
Predicting follower count
#87
abenton
closed
5 years ago
17
Analysis tweets over time
#86
abenton
closed
5 years ago
1
Speed up timeline generation code
#85
abenton
closed
5 years ago
6
Add MTurk labeling agreement statistics to draft
#84
abenton
closed
5 years ago
1
Check that user info was being collected prior to the past two weeks
#83
abenton
closed
5 years ago
2
code for feature extraction
#82
bellecarrell
closed
5 years ago
0
topic distribution at user and follower count interval level
#81
bellecarrell
opened
5 years ago
2
tf-idf per specialization
#80
bellecarrell
closed
5 years ago
0
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