twitterpersona.sentiment_analysis

Module Contents

Functions

sentiment_labler(df, col)

Labelling each row in a given column of tweets/text with positive, negative or neutral sentiment.

count_tweets(df[, proportion])

Count the proportion of different sentiment tweets in a labelled sentiment dataframe
twitterpersona.sentiment_analysis.sentiment_labler(df, col)[source]

Labelling each row in a given column of tweets/text with positive, negative or neutral sentiment.

Parameters:

  • df (pd.DataFrame) – A dataframe that has been pre-processed.

  • col (str) – Column name of the column containing tweets in the dataset.

Returns:

df – Dataframe contains all tweets the corresponding labels.

Return type:

pd.DataFrame

Examples

sentiment_labler(df, “text”)

twitterpersona.sentiment_analysis.count_tweets(df, proportion=True)[source]

Count the proportion of different sentiment tweets in a labelled sentiment dataframe

Parameters:

  • df (pd.DataFrame) – dataframe for each sentiment

  • proportion (bool) – if True: returns the proportion; otherwise, return the counts.

Returns:

A dictionary which calculates the proportion of three sentiments of tweets.

Return type:

dictionary

Examples

labelled_df = sentiment_labler(df, “text”) count_tweets(labelled_df)