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Editorial Citation - Scopus: 1Quality and Reliability Engineering: Trends and Future Directions(Graz Univ Technolgoy, inst information Systems Computer Media-iicm, 2018) Mishra, Alok; Khatri, Sunil Kumar; Kapur, P. K.; Kumar, Uday; Software Engineering[No Abstract Available]Conference Object ISDE 2011 PC Co-chairs' Message(Springer-verlag Berlin, 2011) Mishra, Alok; Muench, Juergen; Colomo-Palacios, Ricardo; Mishra, Deepti[No Abstract Available]Conference Object Agile Methods Adoption in Large Software Development Projects(Ieee, 2016) Mishra, Alok[No Abstract Available]Editorial Citation - WoS: 5Citation - Scopus: 12Future Directions in Agile Research: Alignment and Divergence Between Research and Practice(Wiley, 2017) Mishra, Alok; Garbajosa, Juan; Wang, Xiaofeng; Bosch, Jan; Abrahamsson, Pekka[No Abstract Available]Conference Object Citation - WoS: 1Sustainable Software Engineering: a Move Towards Future(Ieee, 2017) Mishra, Alok[No Abstract Available]Editorial Information Systems in Distributed Environment(Elsevier, 2016) Mishra, Alok; Munch, Jurgen; Lassenius, Casper; Mishra, Deepti[No Abstract Available]Article Citation - WoS: 12Citation - Scopus: 31Sentimental Analysis of Twitter Users From Turkish Content With Natural Language Processing(Hindawi Ltd, 2022) Balli, Cagla; Guzel, Mehmet Serdar; Bostanci, Erkan; Mishra, AlokArtificial Intelligence has guided technological progress in recent years; it has shown significant development with increased academic studies on Machine Learning and the high demand for this field in the sector. In addition to the advancement of technology day by day, the pandemic, which has become a part of our lives since early 2020, has led to social media occupying a larger place in the lives of individuals. Therefore, social media posts have become an excellent data source for the field of sentiment analysis. The main contribution of this study is based on the Natural Language Processing method, which is one of the machine learning topics in the literature. Sentiment analysis classification is a solid example for machine learning tasks that belongs to human-machine interaction. It is essential to make the computer understand people emotional situation with classifiers. There are a limited number of Turkish language studies in the literature. Turkish language has different types of linguistic features from English. Since Turkish is an agglutinative language, it is challenging to make sentiment analysis with that language. This paper aims to perform sentiment analysis of several machine learning algorithms on Turkish language datasets that are collected from Twitter. In this research, besides using public dataset that belongs to Beyaz (2021) to get more general results, another dataset is created to understand the impact of the pandemic on people and to learn about public opinions. Therefore, a custom dataset, namely, SentimentSet (Balli 2021), was created, consisting of Turkish tweets that were filtered with words such as pandemic and corona by manually marking as positive, negative, or neutral. Besides, SentimentSet could be used in future researches as benchmark dataset. Results show classification accuracy of not only up to similar to 87% with test data from datasets of both datasets and trained models, but also up to similar to 84% with small "Sample Test Data" generated by the same methods as SentimentSet dataset. These research results contributed to indicating Turkish language specific sentiment analysis that is dependent on language specifications.Article Citation - WoS: 28Citation - Scopus: 39Effective Communication, Collaboration, and Coordination in Extreme Programming: Human-Centric Perspective in a Small Organization(Wiley, 2009) Mishra, Deepti; Mishra, AlokEffective communication, collaboration, and coordination are important contributing factors in achieving success in agile software development projects. The significance of the workplace environment and tools are immense in effective communication, collaboration, and coordination among people performing software development. In this article, we study how the workplace environment and the effective use of tools like whiteboards, status boards, and so forth for exchanging information improved communication, collaboration, and coordination without compromising the ability to do individual work by developers in a small-scale software development organization. Based on experience and an extensive literature review of communication, collaboration, coordination, and the significance of these in the workplace environment, a survey questionnaire was developed to collect data and observe the effect of these in a small software development organization. Our study indicated appropriate workspace environment has a positive effect on communication, collaboration, and coordination in small organizations developing software using eXtreme Programming (XP). (C) 2009 Wiley Periodicals, Inc.Book Part Citation - WoS: 2Citation - Scopus: 5Curriculum Issues in Industry Oriented Software Engineering Education(Igi Global, 2012) Mishra, Alok; Mishra, DeeptiSoftware engineering education has been emerging as an independent and mature discipline. Accordingly, various studies are being done to provide guidelines for the software engineering education curriculum design. This chapter summarizes the case for the need for software industry related courses and discusses the significance of industry oriented software engineering education to meet the educational objectives of all stakeholders. Software industry oriented curricula for the undergraduate and postgraduate levels are discussed. An industry oriented postgraduate level (Master's degree level) software engineering course is also proposed which includes foundational and applied courses to provide effective training to future software engineers. This will lead to the enhancement of their employment prospects in industrial and allied sectors.Editorial Citation - WoS: 3Citation - Scopus: 3Distributed Development of Information System J.ucs Special Issue(Graz Univ Technolgoy, inst information Systems Computer Media-iicm, 2012) Mishra, Alok; Munch, Jurgen; Mishra, Deepti; Computer Engineering; Software Engineering[No Abstract Available]
