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Facial expression is a major area for non-verbal language in day to day life communication. As the statistical analysis shows only 7 percent of the message in communication was covered in verbal communication while 55 percent transmitted by facial expression. Emotional expression has been a research subject of physiology since Darwin’s work on emotional expression in the 19th century. According to Psychological theory the classification of human emotion is classified majorly into six emotions: happiness, fear, anger, surprise, disgust, and sadness. Facial expressions which involve the emotions and the nature of speech play a foremost role in expressing these emotions. Thereafter, researchers developed a system based on Anatomic of face named Facial Action Coding System (FACS) in 1970. Ever since the development of FACS there is a rapid progress in the domain of emotion recognition. This work is intended to give a thorough comparative analysis of the various techniques and methods that were applied to recognize and identify human emotions. This analysis results will help to identify proper and suitable techniques, algorithms and the methodologies for future research directions. In this paper extensive analysis on various recognition techniques used to identify the complexity in recognizing the facial expression is presented.

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Sentiment Analysis for Software EngineeringHow Far Can We G.docx

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Sentiment Analysis for Software Engineering: How Far Can We Go? Bin Lin Software Institute Università della Svizzera italiana (USI) Switzerland Fiorella Zampetti Department of Engineering University of Sannio Italy Gabriele Bavota Software Institute Università della Svizzera italiana (USI) Switzerland Massimiliano Di Penta Department of Engineering University of Sannio Italy Michele Lanza Software Institute Università della Svizzera italiana (USI) Switzerland Rocco Oliveto STAKE Lab University of Molise Italy ABSTRACT Sentiment analysis has been applied to various software engineering (SE) tasks, such as evaluating app reviews or analyzing developers’ emotions in commit messages. Studies indicate that sentiment analysis tools provide unreliable results when used out-of-the-box, since they are not designed to process SE datasets. The silver bul- let for a successful application of sentiment analysis tools to SE datasets might be their customization to the specific usage context. We describe our experience in building a software library recom- mender exploiting developers’ opinions mined from Stack Overflow. To reach our goal, we retrained—on a set of 40k manually labeled sentences/words extracted from Stack Overflow—a state-of-the-art sentiment analysis tool exploiting deep learning. Despite such an effort- and time-consuming training process, the results were nega- tive. We changed our focus and performed a thorough investigation of the accuracy of commonly used tools to identify the sentiment of SE related texts. Meanwhile, we also studied the impact of different datasets on tool performance. Our results should warn the research community about the strong limitations of current sentiment analysis tools. CCS CONCEPTS • Information systems → Sentiment analysis; KEYWORDS sentiment analysis, software engineering, NLP ACM Reference Format: Bin Lin, Fiorella Zampetti, Gabriele Bavota, Massimiliano Di Penta, Michele Lanza, and Rocco Oliveto. 2018. Sentiment Analysis for Software Engineer- ing: How Far Can We Go?. In ICSE ’18: ICSE ’18: 40th International Conference on Software Engineering , May 27-June 3, 2018, Gothenburg, Sweden. ACM, New York, NY, USA, 11 pages. https://doi.org/10.1145/3180155.3180195 Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected] ICSE ’18, May 27-June 3, 2018, Gothenburg, Sweden © 2018 Copyright held by the owner/author(s). Publication rights licen.

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