Merge pull request #1051 from ajdapretnar/sent-doc

[DOC] Sentiment Analysis: Update dead link

doc/widgets/sentimentanalysis.md

@@ -11,7 +11,7 @@ Predict sentiment from text.
 
 - Corpus: A corpus with information on the sentiment of each document.
 
-**Sentiment Analysis** predicts sentiment for each document in a corpus. It uses Liu & Hu and Vader sentiment modules from [NLTK](http://www.nltk.org/api/nltk.sentiment.html), multilingual sentiment lexicons from the [Data Science Lab](https://sites.google.com/site/datascienceslab/projects/multilingualsentiment), [SentiArt](https://www.frontiersin.org/articles/10.3389/frobt.2019.00053/full) from Arthur Jacobs, and [LiLaH sentiment](http://hdl.handle.net/11356/1318) from Walter Daelemans et al. All of them are lexicon-based. For Liu & Hu, you can choose English or Slovenian version. Vader works only on English. Multilingual sentiment supports several languages, which are listed at the bottom of this page. SentiArt works on English and German. LiLaH sentiment supports Slovenian, Croatian, and Dutch. Custom dictionary enables one to upload custom positive and negative sentiment dictionaries. Custom files should be plain text files (.txt) with each word in its own line.
+**Sentiment Analysis** predicts sentiment for each document in a corpus. It uses Liu & Hu and Vader sentiment modules from [NLTK](http://www.nltk.org/api/nltk.sentiment.html), [multilingual sentiment lexicons](https://aclanthology.org/P14-2063.pdf) from Chen and Skiena, [SentiArt](https://www.frontiersin.org/articles/10.3389/frobt.2019.00053/full) from Arthur Jacobs, and [LiLaH sentiment](http://hdl.handle.net/11356/1318) from Walter Daelemans et al. All of them are lexicon-based. For Liu & Hu, you can choose English or Slovenian version. Vader works only on English. Multilingual sentiment supports several languages, which are listed at the bottom of this page. SentiArt works on English and German. LiLaH sentiment supports Slovenian, Croatian, and Dutch. Custom dictionary enables one to upload custom positive and negative sentiment dictionaries. Custom files should be plain text files (.txt) with each word in its own line.
 
 ![](images/SentimentAnalysis-stamped.png)