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A benchmark study on sentiment analysis for software engineering research.

, , and . MSR, page 364-375. ACM, (2018)

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Emotions and Perceived Productivity of Software Developers at the Workplace., , , and . IEEE Trans. Software Eng., 48 (9): 3326-3341 (2022)A replication study on code comprehension and expertise using lightweight biometric sensors., , , , and . ICPC, page 311-322. IEEE / ACM, (2019)The UNIBA System at the EVALITA 2018 Italian Emoji Prediction Task., and . EVALITA@CLiC-it, volume 2263 of CEUR Workshop Proceedings, CEUR-WS.org, (2018)A benchmark study on sentiment analysis for software engineering research., , and . MSR, page 364-375. ACM, (2018)Using Voice and Biofeedback to Predict User Engagement during Product Feedback Interviews., , , , , and . ACM Trans. Softw. Eng. Methodol., 33 (4): 87:1-87:36 (May 2024)Using Voice and Biofeedback to Predict User Engagement during Requirements Interviews., , , , , and . CoRR, (2021)Towards recognizing the emotions of developers using biometrics: the design of a field study., , , , and . SEmotion@ICSE, page 13-16. IEEE / ACM, (2019)Can We Use SE-specific Sentiment Analysis Tools in a Cross-Platform Setting?, , , , and . MSR, page 158-168. ACM, (2020)Recognizing developers' emotions while programming., , , and . ICSE, page 666-677. ACM, (2020)Emotion detection using noninvasive low cost sensors., , and . ACII, page 125-130. IEEE Computer Society, (2017)