RP-commenting-practices-social-media Replication Package for the paper "What do Developers Discuss about Code Comment Conventions on Social Media?" Structure Paper-presenation.pdf Makar_tool/ Data/ stackoverfow_questions_with_answers_by_tags.csv stackoverfow_tags_metrics.csv apache_mailing_list.csv mailing_lists_ASF_@dev_@users_1.csv mailing_lists_ASF_@dev_@users_2.csv quora.csv sample_stackoverfow_questions_with_answers_by_tags.csv Schemas/ apache_mailing_lists.json quora.json stackoverfow_questions_answers_by_tag.json stackoverfow_tag_count.json stackoverfow_tag_metrics.json RQ1/ LDA_input/ stackoverfow_raw_dataset.csv LDA_output/ Mallet/ output_csv/ docs-in-topics.csv topic-words.csv topics-in-docs.csv topics-metadata.csv output_html/ all_topics.html Docs/ Topics/ RQ2/ datasource_rawdata/ mailing_lists_selection_criteria.csv quora.csv stackoverflow.csv manual_analysis_output/ stackoverflow_quora_taxonomy.xlsx Contents of the Replication Package Paper-presenation.pdf presents the highlights of the work in a presenation. Makar_tool/ contains the data processed using the tool for the study Data/ stackoverfow_questions_with_answers_by_tags.csv - all stackoverflow questions used in the study as stored in Makar stackoverfow_tags_metrics.csv - all data containing the calculations done for stackoverflow tag selection apache_mailing_list.csv - statistically significant sample of mailing_lists_ASF_@dev_@users_1.csv and mailing_lists_ASF_@dev_@users_2.csv used in the study mailing_lists_ASF_@dev_@users_1.csv - mailing list data used in the study as stored in Makar (part 1) mailing_lists_ASF_@dev_@users_2.csv - mailing list data used in the study as stored in Makar (part 2) quora.csv - all quora questions used in the study as stored in Makar sample_stackoverfow_questions_with_answers_by_tags - statistically significant sample of stackoverfow_questions_with_answers_by_tags.csv used in the study Schemas/ apache_mailing_lists.json - data schema used in Makar to store mailing list data quora.json - data schema used in Makar to store quora data stackoverfow_questions_answers_by_tag.json - data schema used in Makar to store stackoverflow questions data stackoverfow_tag_count.json - data schema used in Makar to lookup number of questions per tag available in stackoverflow stackoverfow_tag_metrics.json - data schema used in Makar to stackoverflow tag metrics data RQ1/ - contains the data used to answer RQ1 LDA_input/ - input data used for LDA analysis stackoverfow_raw_dataset.csv - stackoverflow questions used to perform LDA analysis LDA_output/ Mallet/ - contains the LDA output generated by MALLET tool output_csv/ docs-in-topics.csv - documents per topic topic-words.csv - most relevant topic words topics-in-docs.csv - topic probability per document topics-metadata.csv - metadata per document and topic probability output_html/ - Browsable results of mallet output all_topics.html Docs/ Topics/ RQ2/ - contains the data used to answer RQ2 datasource_rawdata/ - contains the raw data for each source mailing_lists_selection_criteria.csv - criteria used to select mailing_lists. quora.csv - contains the processed dataset (like removing HTML tags). To know more about the preprocessing steps, please refer to the reproducibility section in the paper. The data is preprocessed using Makar tool. stackoverflow.csv - contains the processed stackoverflow dataset. To know more about the preprocessing steps, please refer to the reproducibility section in the paper. The data is preprocessed using Makar tool. manual_analysis_output/ stackoverflow_quora_taxonomy.xlsx - contains the classified dataset of stackoverflow and quora and description of taxonomy. Taxonomy - contains the description of the first dimension and second dimension categories. Second dimension categories are further divided into levels, separated by | symbol. stackoverflow-posts - the questions are labelled relevant or irrelevant and categorized into the first dimension and second dimension categories. quota-posts - the questions are labelled relevant or irrelevant and categorized into the first dimension and second dimension categories.