X-Git-Url: https://code.communitydata.science/cdsc_reddit.git/blobdiff_plain/811a0d87c4d394c2c7849a613f6aec2d81e49138..07b0dff9bc0dae2ab6f7fb7334007a5269a512ad:/bots/good_bad_bot.py

diff --git a/bots/good_bad_bot.py b/bots/good_bad_bot.py
deleted file mode 100644
index eb57ff1..0000000
--- a/bots/good_bad_bot.py
+++ /dev/null
@@ -1,74 +0,0 @@
-from pyspark.sql import functions as f
-from pyspark.sql import SparkSession
-from pyspark.sql import Window
-from pyspark.sql.types import FloatType
-import zlib
-
-def zlib_entropy_rate(s):
-    sb = s.encode()
-    if len(sb) == 0:
-        return None
-    else:
-        return len(zlib.compress(s.encode(),level=6))/len(s.encode())
-    
-zlib_entropy_rate_udf = f.udf(zlib_entropy_rate,FloatType())
-
-spark = SparkSession.builder.getOrCreate()
-
-df = spark.read.parquet("/gscratch/comdata/output/reddit_comments_by_author.parquet",compression='snappy')
-
-df = df.withColumn("saidbot",f.lower(f.col("body")).like("%bot%"))
-
-# df = df.filter(df.subreddit=='seattle')
-# df = df.cache()
-botreplies = df.filter(f.lower(df.body).rlike(".*[good|bad] bot.*"))
-botreplies = botreplies.select([f.col("parent_id").substr(4,100).alias("bot_comment_id"),f.lower(f.col("body")).alias("good_bad_bot"),f.col("link_id").alias("gbbb_link_id")])
-botreplies = botreplies.groupby(['bot_comment_id']).agg(f.count('good_bad_bot').alias("N_goodbad_votes"),
-                                                        f.sum((f.lower(f.col('good_bad_bot')).like('%good bot%').astype("double"))).alias("n_good_votes"),
-                                                        f.sum((f.lower(f.col('good_bad_bot')).like('%bad bot%').astype("double"))).alias("n_bad_votes"))
-
-comments_by_author = df.select(['author','id','saidbot']).groupBy('author').agg(f.count('id').alias("N_comments"),
-                                                                                f.mean(f.col('saidbot').astype("double")).alias("prop_saidbot"),
-                                                                                f.sum(f.col('saidbot').astype("double")).alias("n_saidbot"))
-
-# pd_comments_by_author = comments_by_author.toPandas()
-# pd_comments_by_author['frac'] = 500 / pd_comments_by_author['N_comments']
-# pd_comments_by_author.loc[pd_comments_by_author.frac > 1, 'frac'] = 1
-# fractions = pd_comments_by_author.loc[:,['author','frac']]
-# fractions = fractions.set_index('author').to_dict()['frac']
-
-# sampled_author_comments = df.sampleBy("author",fractions).groupBy('author').agg(f.concat_ws(" ", f.collect_list('body')).alias('comments'))
-df = df.withColumn("randn",f.randn(seed=1968))
-
-win = Window.partitionBy("author").orderBy("randn")
-
-df = df.withColumn("randRank",f.rank().over(win))
-sampled_author_comments = df.filter(f.col("randRank") <= 1000)
-sampled_author_comments = sampled_author_comments.groupBy('author').agg(f.concat_ws(" ", f.collect_list('body')).alias('comments'))
-
-author_entropy_rates = sampled_author_comments.select(['author',zlib_entropy_rate_udf(f.col('comments')).alias("entropy_rate")])
-
-parents = df.join(botreplies, on=df.id==botreplies.bot_comment_id,how='right_outer')
-
-win1 = Window.partitionBy("author")
-parents = parents.withColumn("first_bot_reply",f.min(f.col("CreatedAt")).over(win1))
-
-first_bot_reply = parents.filter(f.col("first_bot_reply")==f.col("CreatedAt"))
-first_bot_reply = first_bot_reply.withColumnRenamed("CreatedAt","FB_CreatedAt")
-first_bot_reply = first_bot_reply.withColumnRenamed("id","FB_id")
-
-comments_since_first_bot_reply = df.join(first_bot_reply,on = 'author',how='right_outer').filter(f.col("CreatedAt")>=f.col("first_bot_reply"))
-comments_since_first_bot_reply = comments_since_first_bot_reply.groupBy("author").agg(f.count("id").alias("N_comments_since_firstbot"))
-
-bots = parents.groupby(['author']).agg(f.sum('N_goodbad_votes').alias("N_goodbad_votes"),
-                                          f.sum(f.col('n_good_votes')).alias("n_good_votes"),
-                                          f.sum(f.col('n_bad_votes')).alias("n_bad_votes"),
-                                          f.count(f.col('author')).alias("N_bot_posts"))
-
-bots = bots.join(comments_by_author,on="author",how='left_outer')
-bots = bots.join(comments_since_first_bot_reply,on="author",how='left_outer')
-bots = bots.join(author_entropy_rates,on='author',how='left_outer')
-
-bots = bots.orderBy("N_goodbad_votes",ascending=False)
-bots = bots.repartition(1)
-bots.write.parquet("/gscratch/comdata/output/reddit_good_bad_bot.parquet",mode='overwrite')