Exploring Word Embedding Techniques to Improve Sentiment Analysis of Software Engineering Texts

1. Does the paper propose a new opinion mining approach?

Yes

2. Which opinion mining techniques are used (list all of them, clearly stating their name/reference)?

RNN using undersampling/oversampling, replaced the GN word embeddings with the SOwoStop word embeddings, trained with LinSOData

3. Which opinion mining approaches in the paper are publicly available? Write down their name and links. If no approach is publicly available, leave it blank or None.

No

4. What is the main goal of the whole study?

To improve the training for sentiment analysis of SE artifacts in the context of the use of neural networks customized

5. What the researchers want to achieve by applying the technique(s) (e.g., calculate the sentiment polarity of app reviews)?

predict sentiment polarity of stackoverflow sentences

6. Which dataset(s) the technique is applied on?

LinSOData

7. Is/Are the dataset(s) publicly available online? If yes, please indicate their name and links.

LinSOData: Lin, Bin and Zampetti, Fiorella and Bavota, Gabriele and Di Penta, Massimiliano and Lanza, Michele and Oliveto, Rocco. “Sentiment Analysis For Software Engineering: How Far Can We Go?” In: Proceedings of the 40th International Conference on Software Engineering. ICSE ’18. Gothenburg, Sweden: ACM, 2018, pp. 94–104.

8. Is the application context (dataset or application domain) different from that for which the technique was originally designed?

N/A (new approach)

9. Is the performance (precision, recall, run-time, etc.) of the technique verified? If yes, how did they verify it and what are the results?

Performed ten-fold cross-validation on LinSOData. Using oversampling and undersampling increased the effectiveness of sentiment analysis for negative and positive sentences. Customizing the sentiment classifier to the software domain using software-specific word embeddings does not surpass the results achieved by the generic word embeddings

10. Does the paper replicate the results of previous work? If yes, leave a summary of the findings (confirm/partially confirms/contradicts).

No

11. What success metrics are used?

precision, recall for positive/neutral/negative sentences

12. Write down any other comments/notes here.

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