quantiative and computational text analysis

Question 1

what is quantitative text analysis ?

Answer 1

converting text into numerical values and use statistical analysis to identify patterns trends and relationships within text

Question 2

computational text analysis ?

Answer 2

using automated and semi computational techniques to process analyse and interpret textual data

Question 3

descriptive methods

Answer 3

word clouds , descriptive statistics , KWIK, KEYNESS, lexical dispersion plot

Question 4

KWIK

Answer 4

Key words in context - list of the key words identifying the source text and the word index number within the source text - in which context do key words appear

Question 5

KEYNESS

Answer 5

compares differential associations of key words in a target and reference group - distinguish words between two groups

Question 6

LEXICAL DISPERSION PLOT

Answer 6

VISUALISE the occurrences of particular terms throughout the text - not only how often but where in speech it is used

Question 7

lexical diversity vs density

Answer 7

diversity = measure of how many different words are used in a text
density = measure of the proportion of lexical items

Question 8

WHEN do we use descriptive statistics for text?

Answer 8

-when trying to present characteristics of a corpus
-for explanatory analysis
-when comparing different texts
-trying to measure frequency of certain concepts /eval changes over time

Question 9

DICTIONARY METHODS

Answer 9

-words that hold similar meanings and use multiple categories
-predefine words associated with specific meanings
two components - KEY - label for categories
values- multiple features associated with those categories

Question 10

what do we use dictionary methods for ?

Answer 10

• to measure concept prevalence in text
• measure the extent to which documents belong to certain categories
  -classify documents into categories
• features to measure similarity

Question 11

computational text analysis methods

Answer 11

MACHINE LEARNING - supervised classification - manually code a subset of the data

Question 12

unsupervised classification

Answer 12

discover main themes in an unstructured corpus
-organise collection according to themes - requires no human annotation or prior info
-need to tell about number of topics

Question 13

structural topic model

Answer 13

-allows for the inclusion of arbitrary covariates into generative model
addition of covariates - provides structure
-topics within STM can be correlated