transfer from annonymous repo

MySQL_queries/filter_valid_users

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+select distinct u.id 
+from ghtorrent.users as u, ghtorrent.commits as c, 
+namsor.ght_private as p, namsor.name_parse as np, 
+namsor.origin as o, 
+namsor.gender as g 
+where 
+g.firstName = np.firstName and g.lastName = np.lastName 
+and o.firstName = np.firstName 
+and o.lastName = np.lastName 
+and p.name = np.fullName and p.login = u.login 
+and length(p.name) - length(replace(p.name, ' ', '')) > 0 
+and c.author_id = u.id 
+and p.login NOT REGEXP BINARY '^[A-Z]{8}$' 
+and u.type = 'USR';

MySQL_queries/ght_namsor_s

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+CREATE TABLE `ght_namsor_s` (
+  `id` int(11) NOT NULL DEFAULT '0',
+  `login` varchar(255) CHARACTER SET utf8 NOT NULL,
+  `name` text,
+  `firstName` text,
+  `lastName` text,
+  `email` text,
+  `company` varchar(255) CHARACTER SET utf8 DEFAULT NULL,
+  `created_at` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
+  `type` varchar(255) CHARACTER SET utf8 NOT NULL DEFAULT 'USR',
+  `fake` tinyint(1) NOT NULL DEFAULT '0',
+  `deleted` tinyint(1) NOT NULL DEFAULT '0',
+  `location` varchar(255) CHARACTER SET utf8 DEFAULT NULL,
+  `nameParseScore` float DEFAULT NULL,
+  `country` varchar(255) DEFAULT NULL,
+  `countryAlt` varchar(255) DEFAULT NULL,
+  `countryScore` float DEFAULT NULL,
+  `script` varchar(255) DEFAULT NULL,
+  `countryFirstName` text,
+  `countryLastName` text,
+  `countryScoreFirstName` float DEFAULT NULL,
+  `countryScoreLastName` float DEFAULT NULL,
+  `gender` varchar(255) DEFAULT NULL,
+  `countryGender` varchar(255) DEFAULT NULL,
+  `countryGenderAlt` varchar(255) DEFAULT NULL,
+  `genderScale` float DEFAULT NULL,
+  `gplus_gender` float DEFAULT NULL,
+  `gplus_reliability` float DEFAULT NULL,
+  `genderComputer` float DEFAULT NULL,
+  `do_not_contact` tinyint(1) DEFAULT '0',
+  `friendly` tinyint(1) DEFAULT '0',
+  `first_commit` datetime DEFAULT NULL,
+  KEY `index1` (`id`),
+  KEY `index2` (`login`)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

README.md

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+# icse2019
+
+These Python files were used to calculate social capital ... for paper .....
+
+Required dependencies:
+pickle
+sqlalchemy
+pandas
+scipy
+
+In the MySQL database, there are the following tables:
+users
+commits
+ght_namsor_s (created using the MySQL query provided in `MySQL_queries/ght_namsor_s`
+
+Procedure of running the code: 
+1. Use `MySQL_queries/filter_valid_users` to find valid users. For all valid users, run `determine_gender.py` to determine their genders.
+
+2. Run `sample_user.py` to get a balanced sample of equal number of male and female contributors. The result is saved in `data/uid.list`.
+
+3. Run `setup.py`, which reads files `dict/alias_map_b.dict`,
+`dict/reverse_alias_map_b.dict`, and `data/uid.list`, and generates files
+`data/pid.list`, `data/all_contributors.list`, `dict/contr_projs.dict`,
+`data/all_projs.list`, and `dict/proj_contrs_count.dict`.
+
+4. Run `get_user_info.py`, `get_proj_info.py`, and `get_user_proj_info.py`. They write to `data/results_users.csv`, `data/results_proj.csv`, and `data/results_user_proj.csv` repectively.
+
+5. Run `merge_result.py` to combine these tables. The result will be saved in `data/proj_user_proj.csv`, which will be used for data analysis.