#RhetID Rhetorical Analysis of Text for Author Identification

RhetID analyzes your text for elements of famous authors to decide who you most wrtie like.

Packages

POS

• The pos package is used to house all the Part of Speech tagging classes.
• Note that part of speech tagging relies on the .map and .set files in PosFiles.

Zipf

• The zipf package is used to house all the classes for implementing Zipf's law.
• Note the implementation must take a word at a time to reduce algorithmic complexity.

Author

• The author package will house data types for holding authors statistics and trends.
• Will be done statically in the same manner as POS.

Elements

Name Change Pending

• The elements package will house the shorter algorithms to track various other elements of textual analysis.
• Likely will implement a data sructure that will analyze all elements in a single add function.

Shakespeare

Type	Hamlet	Macbeth
NN/S:	2.250208507089241	2.8117859290438965
PN/S:	0.8237420072282458	2.2561635598316294
PP/S:	0.8215179316096747	0.761876127480457
VB/S:	1.2643869891576314	1.3878532772098617
JJ/S:	0.6396997497914929	0.6806975345760673
RB/S:	0.5440644981929386	0.5892964521948286
Words:	34852	20943
Sentences:	3597	1663
AvgSent:	9.689185432304699	12.593505712567648
./W	0.08097096292895672	0.06670486558754715
?/W	0.012423964191438082	0.011746168170749176
"/W	9.181682543326064E-4	0.0023874325550303204
!/W	0.009755537702283943	8.594757198109154E-4
--/W	0.020056237805577873	3.819892088048513E-4
;/W	0.020056237805577873	0.0027694217638351715
,/W	0.09640766670492368	0.10108389437998376

Jane Austen

Type	Pride and Prejudice	Emma
NN/S:	3.515981012658228	3.0055988582720388
PN/S:	1.292879746835443	1.242726973323087
PP/S:	1.6463607594936709	1.5689976945877704
VB/S:	2.850632911392405	2.6112635854649247
JJ/S:	1.9474683544303797	1.859260072455813
RB/S:	1.5727848101265822	1.5955648259962674
Words:	126482	165231
Sentences:	6320	9109
AvgSent:	20.012974683544304	18.13931276759249