This document outlines steps for analyzing social media text data using various tools like Crimson Hexagon, Python, and ConText: 1. Collect 10,000 tweets from @realDonaldTrump using Crimson Hexagon and export them as a CSV file. 2. Clean the tweet text by removing stopwords, punctuation, lowercase conversion, and stemming. 3. Perform analyses like term frequency, topic modeling, sentiment analysis and generate visualizations like word clouds. 4. The goal is to tell a story by extracting insights from Donald Trump's tweets.

1. SMAC LAB, LSU
OCT 19, 2018
SMAC Talks
Telling Stories from Social Media Text 1
Instructor: Dr. Ke (Jenny) Jiang

2. Telling Stories from Social Media Text 1
Collect Text Data
Clean Text
Text Analysis
Visualization
Python, TCAT, Crimson Hexagon…
Remove Stop Words, Stemming
Replacing “/”, “@” and “|” with space
Convert the text to lower case
Remove punctuations
Frequency Analysis, Sentiment Analysis
Entity Detection, Topic Modeling
Word Clouds, Semantic Network Analysis
R, Gephi
Tell a Story

3. Step 1: Collect Text Data Using Crimson Hexagon
Log in Crimson Hexagon

4. Step 1: Collect Text Data Using Crimson Hexagon
Go to Forsight

5. Step 1: Collect Text Data Using Crimson Hexagon
Click @realDonaldTrump

6. Step 1: Collect Text Data Using Crimson Hexagon
Manage — Bulk Export

7. Step 1: Collect Text Data Using Crimson Hexagon
Export 10,000 posts

8. Step 1: Collect Text Data Using Crimson Hexagon
Open exported file — Save as trump.csv

9. Step 1: Collect Text Data Using Crimson Hexagon
Open trump.csv — Delete the first line

10. Step 2: Create/Load a text file
a. Set Working Directory — Directory for trump.csv

11. b. Get a Sample
Step 3: Create/Load a Text File
Output

12. Step 4: Install and load the Required Packages

13. Create a text Corpus
Step 5: Load the Data as a Corpus
Output

14. Replacing “/”, “@” and “|” with space
Step 6: Clean Text
Output

15. Convert the text to lower case
Step 6: Clean Text
Output

16. Remove numbers
Step 6: Clean Text
Output

17. Remove english common stop-words
Text Bag of Words Clean
Step 6: Clean Text

18. Remove english common stop-words
Step 6: Clean Text
Output

19. Remove your own stop word
Step 6: Clean Text
Output

20. Remove punctuations
Step 6: Clean Text
Output

21. Eliminate Extra White Spaces
Step 6: Clean Text
Output

22. Stemming
Loves
Loved
Loving
Love s
Love d
Love ing
Love
Step 6: Clean Text
Stemming

23. Stemming
Step 6: Clean Text
Output

24. Frequency
Step 7: Build a Term-Document Matrix
Output

25. Frequency Visualization
Step 7: Build a Term-Document Matrix
Output

26. Generate the Word cloud
Step 8: Build a Term-Document Matrix
Output

27. Step 9: Save Text Corpus to .csv

28. Step 10: Download and Open ConText
http://context.ischool.illinois.edu/download.php#download

29. Preparation
Creating two folders: raw data, results
move the trumpsemiclean.csv to the raw data folder

30. Parse CSV Files
ConText Tutorials

31. Parse CSV Files
ConText Tutorials

32. Parse CSV Files
ConText Tutorials

33. Parse CSV Files
ConText Tutorials

34. Parse CSV Files
ConText Tutorials

35. Parse CSV Files
ConText Tutorials

36. Parse CSV Files
ConText Tutorials

37. Parse CSV Files
ConText Tutorials

38. Stemming
ConText Tutorials

39. Stemming
ConText Tutorials

40. Stemming
ConText Tutorials

41. Stemming
ConText Tutorials

42. Stemming
ConText Tutorials

43. Frequency
ConText Tutorials

44. Frequency
ConText Tutorials

45. Frequency
ConText Tutorials

46. Frequency
ConText Tutorials

47. Frequency
ConText Tutorials

48. Bigram
ConText Tutorials

49. Bigram
ConText Tutorials

50. Bigram
ConText Tutorials

51. Bigram
ConText Tutorials

52. Bigram
ConText Tutorials

53. Topic Modeling
ConText Tutorials

54. Topic Modeling
ConText Tutorials

55. Topic Modeling
ConText Tutorials

56. Topic Modeling
ConText Tutorials

57. Topic Modeling
ConText Tutorials

58. Topic Modeling
ConText Tutorials

59. Sentiment Analysis
ConText Tutorials

60. Sentiment Analysis
ConText Tutorials

61. Sentiment Analysis
ConText Tutorials

62. Sentiment Analysis
ConText Tutorials

63. Sentiment Analysis
ConText Tutorials

64. Sentiment Analysis
ConText Tutorials

65. Word Clouds of Topics and Sentiment
ConText Tutorials

66. Word Clouds of Topics and Sentiment
ConText Tutorials

67. Word Clouds of Topics and Sentiment
ConText Tutorials

68. Word Clouds of Topics and Sentiment
ConText Tutorials

69. Word Clouds of Topics and Sentiment
ConText Tutorials

70. Word Clouds of Topics and Sentiment
ConText Tutorials

71. Word Clouds of Topics and Sentiment
ConText Tutorials

72. Word Clouds of Topics and Sentiment
ConText Tutorials

73. Word Clouds of Topics and Sentiment
ConText Tutorials

74. Entity Detection
ConText Tutorials

75. Entity Detection
ConText Tutorials

76. Entity Detection
ConText Tutorials

77. Entity Detection
ConText Tutorials

78. Entity Detection
ConText Tutorials

79. Entity Detection
ConText Tutorials

80. Entity Detection
ConText Tutorials

81. Results
ConText Tutorials