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medium-fCC-data/README.md

@@ -8,13 +8,35 @@ Collected datasets about fCC in Medium.
 
 # projects & datasets
 
-* dataset: titles of articles in freeCodeCamp Medium, `fccmediumTitles - Cleaned_Data.tsv` (tab-separated file) curated by @evaristoc
+* dataset: stats of titles of articles in freeCodeCamp Medium, `fccmediumTitles - Cleaned_Data.tsv` (tab-separated file) curated by @evaristoc
   * data collected before 12-Oct-2016
   * "Quartier" : quartier of the year
   * "date"  : as "MM yyyy"
-  * "Title" : title of the article
-  * "Views"  : number of Views as defined by Medium Team, "*the number of people who have looked at a post*"
-  * "Reads" : number of Reads as defined by Medium Team, "*how many have read the entire story*"
+  * "Title" : unparsed title of the article
   * "Recommends"  : number of Recommends as defined by Medium Team by the date the data was collected
-  * "Views\_more\_than\_1000" : when Views were more than 1000, 0=False / 1=True
   * "Read ratio"  : percentage of people who view the article and then read it, "*difference between your reads and views*"
+
+* dataset: stats of titles of articles in freeCodeCamp Medium + title class, `medium_titles - rawdata.tsv` (tab-separated file) curated by @evaristoc  * data about titles between Jan-2016 and Jan-2017
+  * "order" : acquisition order (by date)
+  * "inv-ord"  : inverted order
+  * "selection"  : for analytical purposes, 0 or 1
+  * "CollTitle" : title of the article, unparsed
+  * "CorrectedTitle" : parsed CollTitle
+  * "OrigRecommends"  : unparsed number of Recommends as defined by Medium Team by the date the data was collected
+  * "classification" :
+	* TECH : technical
+	* MOT : motivational
+	* SEC : security
+	* JOB : job-related
+	* CS  : computer science
+	* WD  : web development
+	* DES : design
+	* PM  : project management
+	* DS  : data science
+	* FCC : institutional (about fCC)
+	* AD  : advertising
+	* CB  : Code Briefings
+	* OTHER : other
+  * "Recommends"  : parsed number of Recommends as defined by Medium Team by the date the data was collected
+  * "Class_WD" : articles with the WD class; 0=False,1=True
+  * "Class_WD&CS" : articles with either the WD class or the CS class; 0=False,1=True