Spammer.py -

: Calculate metrics like word density, character counts, and punctuation frequency to distinguish between legitimate users and bots.

In academic papers regarding network intrusion, similar naming conventions are used for tools that test system vulnerabilities: spammer.py

: Tag accounts or comments where the percentage of unique words is exceptionally low (e.g., < 30%), a common indicator of automated spam. : Calculate metrics like word density, character counts,

: Use libraries like NLTK to tokenize sentences and analyze the POS (Part-of-Speech) tags of suspected spam messages to find structural anomalies. Network Security and Malware Research : Calculate metrics like word density