Update README.md

Author: maitetaboada

README.md

@@ -162,7 +162,7 @@ The fields in this CSV are same as that of gnm_comments.csv.
 
 ## <a name="constructiveness"></a>SFU constructiveness and toxicity corpus
 
-We annotated a subset of SOCC for constructiveness and toxicity. The annotated corpus is organized as a CSV and contains 1,043 annotated comments in responses to 10 different articles covering a variety of subjects: technology, immigration, terrorism, politics, budget, social issues, religion, property, and refugees. For half of the articles, we included only top-level comments. For the other half, we included both top-level comments and responses. We used CrowdFlower (https://www.crowdflower.com/) as our crowdsourcing annotation platform and annotated the comments for constructiveness. We asked the annotators to first read the articles, and then to tell us whether the displayed comment was constructive or not. 
+We annotated a subset of SOCC for constructiveness and toxicity. The annotated corpus is organized as a CSV and contains 1,043 annotated comments in responses to 10 different articles covering a variety of subjects: technology, immigration, terrorism, politics, budget, social issues, religion, property, and refugees. For half of the articles, we included only top-level comments. For the other half, we included both top-level comments and responses. We used CrowdFlower (then Figure Eight, now Appen) as our crowdsourcing annotation platform and annotated the comments for constructiveness. We asked the annotators to first read the articles, and then to tell us whether the displayed comment was constructive or not. 
 
 For toxicity, we asked annotators a multiple-choice question, *How toxic is the comment?* Four answers were possible: