Name
Abstract | ||
|---|---|---|
There is currently a lack of research concerning whether Emotional Classification (EC) research on a language is applicable to other languages. If this is the case then we can greatly reduce the amount of research needed for different languages. Therefore, we propose a framework to answer the following null hypothesis: The change in classification accuracy for Emotional Classification caused by changing a single preprocessor or classifier is independent of the target language within a significance level of p = 0.05. We test this hypothesis using an English and a Danish data set, and the classification algorithms: Support-Vector Machine, Naive Bayes, and Random Forest. From our statistical test, we got a p-value of 0.12852 and could therefore not reject our hypothesis. Thus, our hypothesis could still be true. More research is therefore needed within the field of cross-language EC in order to benefit EC for different languages. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.15439/2019F143 | 2019 Federated Conference on Computer Science and Information Systems (FedCSIS) |
Keywords | Field | DocType |
Sentiment Analysis,Emotional Classification,Text-to-Emotion Analysis,Cross-Language Analysis,Natural Language Processing | Naive Bayes classifier,Null hypothesis,Computer science,Sentiment analysis,Preprocessor,Artificial intelligence,Classifier (linguistics),Statistical classification,Random forest,Statistical hypothesis testing,Machine learning | Conference |
ISSN | ISBN | Citations |
2325-0348 | 978-1-5386-8005-6 | 0 |
PageRank | References | Authors |
0.34 | 2 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexander Christoffer Eilertsen | 1 | 0 | 0.34 |
| Dennis Højbjerg Rose | 2 | 0 | 0.34 |
| Peter Langballe Erichsen | 3 | 0 | 0.34 |
| Rasmus Engesgaard Christensen | 4 | 0 | 0.34 |
| Rudra Pratap Deb Nath | 5 | 0 | 0.34 |