cometaNLP 0.0.4

A NLP data and text analysis tool for Italian, Dutch, and English social media comments.

cometaNLP

A NLP Comments Extraction and Text Analysis tool for Italian, Dutch, and English social media comments.

Installation

Windows

py -m pip install cometaNLP

Unix\MacOS

python3 -m pip install cometaNLP

.ipynb

!pip install cometaNLP

Supported languages

Functions

cometa is composed by one main module named COMETA. The module has two main class methods:

(1) get_dictionary

    """A class method that applies a series of tranformations to csv and tsv files
    and returns a dictionary
    
    get_dictionary() reads .csv and .tsv file, applies the functions and methods within the
    the COMETA module to the column contaning the comments/text in the dataframe
    in meaningful order, and finally converts it into a dictionary by index according to the following format:
    {index -> {column -> value}}. The dictionary contains relevant information
    for each comment in the dataset.
    To make the function as comprehensive as possible, the user is asked to enter
    whether the csv/tsv file has a header or not and the index of the column
    on which they wish to apply the transformations. The column should be the one containing the comments\text
    data that the user whishes to analyze.
    
    Args:
        self: reference to the current instance of the class
        file_type (str): A string (csv/tsv)
        file_path (str): A string containing a file path to a csv/tsv file
        data_frame (bool): If set to true, the function returns additionally pandas DataFrame object
                           rather than a dictionary
    
    Returns:
        output (dict): A nested dictionary {index -> {column -> value}} containing
                       relevant data and metadata for each comment in the input dataframe
    """

(2) gert_summary

    """A class method that returns the relevant data comparison based on grouping 
    comparison (e.g., X v. Y) rather than for each comment individually.
    
    get_summary() is built upon the get_dictionary method. If visualize is set to True, it also shows a simple visualization of all the
    summarized data. It compares average number of emojis, hashtags,
    urls, user tags, length, type-token ratio, content-function ratio for
    two classes of comments.
    Args:
        self: reference to the current instance of the class
        file_type (str): A string (csv/tsv)
        file_path (str): A string containing a file path to a csv/tsv file
    
    Returns:
        tuple: a tuple of values.
    """

And a subclass functionality to analyze single instances of text:

(3) get_data

    """A class method that operates on the text level to extract data and metadata from a comment. It applies a set of tranfromartion to it based on
    boolean arguments and returns a dictionary contatining the relevant information. If visualization is set to true, it 
    
    get_data() is built upon the get_dictionary method. It applies the the same set of transformation on the string level.
    The user can choose which transformations
    to apply and which to not. If visualize is set to True, it also shows a simple visualization of the pos-tags.
    
    Args:
        self: reference to the current instance of the class
        input_string: Any string
        remove_punctuation (bool): Optionally choose whether to keep (False) or remove (True) punctuation from the input text
        remove_emojis (bool): Optionally choose whether to keep (False) or remove (True) emojis from the input text
        remove_stopwords (bool): Optionally choose whether to keep (False) or remove (True) stopwords from the input text
        TTR (bool): Optionally choose whether to calculate (True) or not (False) the input text TTR
        CFR (bool): Optionally choose whether to calculate (True) or not (False) the input text CFR
        lemmatize (bool): Optionally choose whether to lemmatize (True) or not (False) the input text
        pos (bool): Optionally choose whether to pos-tag (True) or not (False) the input text
        visualize (bool): If set to true, visualizes the pos-tags using nltk color schemes.
    Returns:
        dictionary: a dictionary containing the relevant data and metadata for the input text
    """

Authors

• Leonardo Grotti

Q&A

Q: Why does cometa start from distribution 0.0.3?

A: The first two distributions of the package were erased due to some naming conflicts.