Update README.md

README.md

@@ -115,7 +115,38 @@
 
 ### Citation Information
 
-[More Information Needed]
+```
+@inproceedings{moudjari-etal-2020-algerian,
+    title = "An {A}lgerian Corpus and an Annotation Platform for Opinion and Emotion Analysis",
+    author = "Moudjari, Leila  and
+      Akli-Astouati, Karima  and
+      Benamara, Farah",
+    editor = "Calzolari, Nicoletta  and
+      B{\'e}chet, Fr{\'e}d{\'e}ric  and
+      Blache, Philippe  and
+      Choukri, Khalid  and
+      Cieri, Christopher  and
+      Declerck, Thierry  and
+      Goggi, Sara  and
+      Isahara, Hitoshi  and
+      Maegaard, Bente  and
+      Mariani, Joseph  and
+      Mazo, H{\'e}l{\`e}ne  and
+      Moreno, Asuncion  and
+      Odijk, Jan  and
+      Piperidis, Stelios",
+    booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
+    month = may,
+    year = "2020",
+    address = "Marseille, France",
+    publisher = "European Language Resources Association",
+    url = "https://aclanthology.org/2020.lrec-1.151",
+    pages = "1202--1210",
+    abstract = "In this paper, we address the lack of resources for opinion and emotion analysis related to North African dialects, targeting Algerian dialect. We present TWIFIL (TWItter proFILing) a collaborative annotation platform for crowdsourcing annotation of tweets at different levels of granularity. The plateform allowed the creation of the largest Algerian dialect dataset annotated for both sentiment (9,000 tweets), emotion (about 5,000 tweets) and extra-linguistic information including author profiling (age and gender). The annotation resulted also in the creation of the largest Algerien dialect subjectivity lexicon of about 9,000 entries which can constitute a valuable resources for the development of future NLP applications for Algerian dialect. To test the validity of the dataset, a set of deep learning experiments were conducted to classify a given tweet as positive, negative or neutral. We discuss our results and provide an error analysis to better identify classification errors.",
+    language = "English",
+    ISBN = "979-10-95546-34-4",
+}
+```
 
 ### Contributions