Learning Social Media Analytics with R

Cover
......Page 1
Copyright......Page 3
Credits......Page 4
About the Author......Page 5
About the Reviewer......Page 8
www.PacktPub.com......Page 9
Customer Feedback......Page 10
Table of Contents......Page 12
Preface......Page 20
Chapter 1: Getting Started with R and Social Media Analytics......Page 26
Understanding social media......Page 27
Advantages and significance......Page 29
Disadvantages and pitfalls......Page 31
Social media analytics......Page 32
A typical social media analytics workflow......Page 33
Data processing and normalization......Page 34
Data analysis......Page 35
Opportunities......Page 36
Challenges......Page 37
Getting started with R......Page 38
Environment setup......Page 39
Data types......Page 41
Vectors......Page 43
Arrays......Page 45
Matrices......Page 46
Lists......Page 47
DataFrames......Page 49
Built-in functions......Page 51
User-defined functions......Page 52
Looping constructs......Page 53
Conditional constructs......Page 54
apply......Page 56
sapply......Page 58
tapply......Page 59
mapply......Page 60
Visualizing data......Page 61
Getting help......Page 63
Data analytics......Page 64
Analytics workflow......Page 65
Machine learning techniques......Page 67
Supervised learning......Page 68
Text analytics......Page 69
Summary......Page 70
Chapter 2: Twitter – What\'s Happening with 140 Characters......Page 72
Understanding Twitter......Page 73
APIs......Page 74
Registering an application......Page 75
Connecting to Twitter using R......Page 78
Extracting sample Tweets......Page 80
Trend analysis......Page 81
Sentiment analysis......Page 91
Sentiment polarity......Page 92
Features......Page 93
Sentiment analysis in R......Page 94
Follower graph analysis......Page 104
Challenges......Page 111
Summary......Page 112
Chapter 3: Analyzing Social Networks and Brand Engagements 
with Facebook......Page 114
Understanding the Graph API......Page 116
Understanding Rfacebook......Page 119
Data access challenges......Page 120
Analyzing your personal social network......Page 121
Basic descriptive statistics......Page 122
Analyzing mutual interests......Page 125
Build your friend network graph......Page 127
Visualizing your friend network graph......Page 128
Analyzing node properties......Page 129
Degree......Page 130
Closeness......Page 132
Betweenness......Page 133
Cliques......Page 134
Communities......Page 135
Analyzing an English football social network......Page 139
Basic descriptive statistics......Page 141
Visualizing the network......Page 144
Analyzing network properties......Page 145
Page distances......Page 146
Density......Page 147
Coreness......Page 148
Analyzing node properties......Page 149
Closeness......Page 150
Betweenness......Page 151
Visualizing correlation among centrality measures......Page 152
Eigenvector centrality......Page 154
PageRank......Page 155
HITS authority score......Page 156
Page neighbours......Page 157
Cliques......Page 158
Communities......Page 159
Getting the data......Page 164
Curating the data......Page 165
Visualizing post counts per page......Page 166
Visualizing post counts by post type per page......Page 167
Visualizing average likes by post type per page......Page 168
Visualizing average shares by post type per page......Page 169
Visualizing page engagement over time......Page 170
Visualizing user engagement with page over time......Page 171
Trending posts by user likes per page......Page 173
Trending posts by user shares per page......Page 174
Top influential users on popular page posts......Page 175
Summary......Page 177
Chapter 4: Foursquare – Are You Checked in Yet?......Page 178
Foursquare – the app and data......Page 179
Foursquare APIs – show me the data......Page 180
Creating an application – let me in......Page 181
Data access – the twist in the story......Page 182
Getting category data – introduction to JSON parsing and data extraction......Page 183
Getting the data – the usual hurdle......Page 188
Getting data for a city – geometry to the rescue......Page 189
Analysis – the fun part......Page 192
Basic descriptive statistics – the usual......Page 193
Framing the recommendation problem......Page 199
Building our restaurant recommender......Page 200
Extracting tips data – the go to step......Page 205
The actual data......Page 207
Basic descriptive statistics......Page 208
The final rankings......Page 212
Venue graph – where do people go next?......Page 214
Challenges for Foursquare data analysis......Page 217
Summary......Page 218
Chapter 5: Analyzing Software Collaboration Trends I – Social Coding with GitHub......Page 220
Environment setup......Page 221
Understanding GitHub......Page 222
Using the rgithub package for data access......Page 225
Registering an application on GitHub......Page 226
Accessing data using the GitHub API......Page 228
Analyzing weekly commit frequency......Page 231
Analyzing commit frequency distribution versus day of the week......Page 233
Analyzing daily commit frequency......Page 235
Analyzing weekly commit frequency comparison......Page 236
Analyzing weekly code modification history......Page 238
Retrieving trending repositories......Page 240
Analyzing repository trends......Page 243
Analyzing trending repositories created over time......Page 244
Analyzing trending repositories updated over time......Page 246
Analyzing repository metrics......Page 248
Visualizing repository metric distributions......Page 250
Analyzing repository metric correlations......Page 251
Analyzing relationship between stargazer and repository counts......Page 253
Analyzing relationship between stargazer and fork counts......Page 254
Analyzing relationship between total forks, repository count, and health......Page 257
Visualizing top trending languages......Page 258
Visualizing top trending languages over time......Page 260
Analyzing languages with the most open issues......Page 262
Analyzing languages with the most open issues over time......Page 263
Analyzing languages with the most helpful repositories......Page 265
Analyzing languages with the highest popularity score......Page 267
Analyzing language correlations......Page 269
Visualizing top contributing users......Page 272
Analyzing user activity metrics......Page 274
Summary......Page 278
Chapter 6: Analyzing Software Collaboration Trends II - Answering Your Questions with StackExchange......Page 280
Understanding StackExchange......Page 281
Data access......Page 282
The StackExchange data dump......Page 283
Contents of data dumps......Page 284
Quick overview of the data in data dumps......Page 285
Getting started with data dumps......Page 289
Data Science and StackExchange......Page 290
Demographics and data science......Page 299
Challenges......Page 305
Summary......Page 306
A Flickr-ing world......Page 308
Creating the Flickr app......Page 310
Connecting to R......Page 313
Getting started with Flickr data......Page 316
Understanding Flickr data......Page 317
Understanding more about EXIF......Page 318
Understanding interestingness – similarities......Page 326
Elbow method......Page 327
Silhouette method......Page 328
Preparing the data......Page 335
Building the classifier......Page 339
Challenges......Page 342
Summary......Page 343
Chapter 8: News – The Collective 
Social Media!......Page 344
News data – news is everywhere......Page 345
Accessing news data......Page 346
Creating applications for data access......Page 347
Data extraction – not just an API call......Page 348
The API call and JSON monster......Page 349
Sentiment trend analysis......Page 356
Getting the data – not again......Page 357
Basic descriptive statistics – the usual......Page 358
Numerical sentiment trends......Page 361
Emotion-based sentiment trends......Page 364
Topic modeling......Page 368
Getting to the data......Page 369
Basic descriptive analysis......Page 370
Topic modeling for Mr. Trump\'s phases......Page 373
Pre-processing the data......Page 374
The modeling part......Page 375
Analysis of topics......Page 376
Summarizing news articles......Page 378
Understanding LexRank......Page 379
Summarizing articles with lexRankr......Page 380
Challenges to news data analysis......Page 385
Summary......Page 386
Index......Page 388