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This is a page about some more technical aspects of an application whose main page is: '''[[Twitter Analysis DB]]'''. | This is a page about some more technical aspects of an application whose main page is: '''[[Twitter Analysis DB]]'''. | ||
| − | + | = The Database = | |
| + | The application is designed so that using it does not require writing any SQL ( Structured Query Language ), however, some familiarity with SQL and relational databases may be useful. This is not an introduction to SQL but is a description of some of the ways it has been applied in this application. | ||
| + | == Tweets == | ||
| + | == Concordance == | ||
| + | Commonly abbreviated in the app as concord, it is a table generated from the tweets by extracting each "word" of the tweet. "Word" is in quotes because quite a bit of processing is involved in determining what is a word. The simple way would be to just break the tweets up on blank spaces, but what is actually done is a bit more complicated as described in [[TBD]] | ||
| + | == Words == | ||
| + | |||
| + | This is a table of words taken from common usage and then loaded into a database table "words" | ||
[[Category:Python Projects]] [[category:Python]] [[Category:Twitter Analysis DB]] | [[Category:Python Projects]] [[category:Python]] [[Category:Twitter Analysis DB]] | ||
