We need a Craigslist scraper and parser with (source code; preferably python) that automatically archives multiple RSS feeds from Craigslist.
Running the parsed on the scraped logfile should provide word usage frequency based on gender of poster (extracted from the w4m or m4w header), city, day of posting. The program should allow the user to choose a range of dates (extracted from the timestamps) to pull the statistics from.
Outputs: (1) XML files with the archived feeds for each city and craigslist category
(2) Daily CSV files listing 100 most frequent words categorized by each gender , city, and age group (excluding articles and common modifiers like "a" "an" "the" "for" etc).
An example text file would look like this:
header: 07-01-2009,female, atlanta, 20-25
CSV files should also be generated for all cities, and all age groups.
Headers for these files would look like this
header: 07-01-2009,female, all, 20-25
header: 07-01-2009, female, miami, all
header: 07-01-2009, female, all, all