Issue to handle with Topics extractions

[MastafaF]

We need to handle topics with duplicated keywords.

The two snippets below give different statistics for the same topic money.

Will try to follow up with a PR.

convention_df = st.SampleCorpora.ConventionData2012.get_data() 

topic_model = {
  'money': ['money', 'money', 'money', 'money', 'bank','banks','finances','financial','loan','dollars','income'],
  'jobs':['jobs','workers','labor','employment','worker','employee','job'],
  'patriotic':['america','country','flag','americans','patriotism','patriotic'],
  'family':['mother','father','mom','dad','sister','brother','grandfather','grandmother','son','daughter']
}

import scattertext as st

topic_feature_builder = st.FeatsFromTopicModel(topic_model)

convention_df['parse'] = convention_df['text'].apply(st.whitespace_nlp_with_sentences)

topic_corpus = st.CorpusFromParsedDocuments(
    convention_df,
    category_col='party',
    parsed_col='parse',
    feats_from_spacy_doc=topic_feature_builder
).build()

html = st.produce_scattertext_explorer(
    topic_corpus,
    category='democrat',
    category_name='Democratic',
    not_category_name='Republican',
    width_in_pixels=1000,
    metadata=convention_df['speaker'],
    use_non_text_features=True,
    use_full_doc=True,
    pmi_threshold_coefficient=0,
    topic_model_term_lists=topic_feature_builder.get_top_model_term_lists()
)

with open("tst_remove_2.html", 'w') as f:
    f.write(html)

convention_df = st.SampleCorpora.ConventionData2012.get_data() 

topic_model = {
  'money': ['money', 'bank','banks','finances','financial','loan','dollars','income'],
  'jobs':['jobs','workers','labor','employment','worker','employee','job'],
  'patriotic':['america','country','flag','americans','patriotism','patriotic'],
  'family':['mother','father','mom','dad','sister','brother','grandfather','grandmother','son','daughter']
}

import scattertext as st

topic_feature_builder = st.FeatsFromTopicModel(topic_model)

convention_df['parse'] = convention_df['text'].apply(st.whitespace_nlp_with_sentences)

topic_corpus = st.CorpusFromParsedDocuments(
    convention_df,
    category_col='party',
    parsed_col='parse',
    feats_from_spacy_doc=topic_feature_builder
).build()

html = st.produce_scattertext_explorer(
    topic_corpus,
    category='democrat',
    category_name='Democratic',
    not_category_name='Republican',
    width_in_pixels=1000,
    metadata=convention_df['speaker'],
    use_non_text_features=True,
    use_full_doc=True,
    pmi_threshold_coefficient=0,
    topic_model_term_lists=topic_feature_builder.get_top_model_term_lists()
)

with open("tst_remove_2.html", 'w') as f:
    f.write(html)

[JasonKessler]

Please follow the instructions for reporting a bug in the issue template.

Once you do so, we can reopen the issue and verify there's a problem.