Miikka Kuutila

The evolution of sentiment analysis—A review of research topics, venues, and top cited papers

Sentiment analysis is one of the fastest growing research areas in computer science, making it challenging to keep track of all the activities in the area. We present a computer-assisted literature review, where we utilize both text mining and qualitative coding, and analyze 6,996 papers from Scopus. We find that the roots of sentiment analysis are in the studies on public opinion analysis at the beginning of 20th century and in the text subjectivity analysis performed by the computational linguistics community in 1990s. However, the outbreak of computer-based sentiment analysis only occurred with the availability of subjective texts on the Web. Consequently, 99% of the papers have been published after 2004. Sentiment analysis papers are scattered to multiple publication venues, and the combined number of papers in the top-15 venues only represent ca. 30% of the papers in total. We present the top-20 cited papers from Google Scholar and Scopus and a taxonomy of research topics. In recent years, sentiment analysis has shifted from analyzing online product reviews to social media texts from Twitter and Facebook. Many topics beyond product reviews like stock markets, elections, disasters, medicine, software engineering and cyberbullying extend the utilization of sentiment analysis

TestAWARE: A Laboratory-Oriented Testing Tool for Mobile Context-Aware Applications

Although mobile context instrumentation frameworks have simplified the development of mobile context-aware applications, it remains challenging to test such applications. In this paper, we present TestAWARE that enables developers to systematically test context-aware applications in laboratory settings. To achieve this, TestAWARE is able to download, replay and emulate contextual data on either physical devices or emulators. To support both white -box and black-box testing, TestAWARE has been implemented as a novel structure with a mobile client and code library. In blackbox testing scenarios, developers can manage data replay through the mobile client, without writing testing scripts or modifying the source code of the targeted application. In white-box testing scenarios, developers can manage data replay and test functional/non-functional properties of the targeted application by writing testing scripts using the code library. We evaluated TestAWARE by quantifying its maximal data replay speed, and by conducting a user study with 13 developers. We show that TestAWARE can overcome data synchronisation challenges, and found that PC-based emulators can replay data significantly faster than physical smartphones and tablets. The user study highlights the usefulness of TestAWARE in the systematic testing of mobile context-aware applications in laboratory settings.

Daily questionnaire to assess self-reported well-being during a software development project

According to authors best knowledge, this workshop paper makes two novel extensions to software engineering research. First, we create and execute a daily questionnaire monitoring the work well-being of software developers through a period of eight months. Second, we utilize statistical methods developed for discovering psychological dynamics to analyze this data. Our questionnaire includes elements from job satisfaction surveys and one software development specific element. The data were collected every day for a period of 8 months in a single software development project producing 526 answers from eight developers. The preliminary analysis shows the strongest correlations between hurry and interruptions. Additionally, we constructed temporal and contemporaneous network models used for discovering psychological dynamics from the questionnaire responses. In the future, we will try to establish links between the survey responses and the measures collected by conducting software repository mining and sentiment analysis.

How to validate mobile crowdsourcing design? leveraging data integration in prototype testing

Mobile crowdsourcing applications often run in dynamic environments. Due to limited time and budget, developers of mobile crowdsourcing applications sometimes cannot completely test their prototypes in real world situations. We describe a data integration technique for developers to validate their design in prototype testing. Our approach constructs the intended context by combining real-time, historical and simulated data. With correct context-aware design, mobile crowdsourcing applications presenting crowdsourcing questions in relevant context to users are likely to obtain high response quality.

Using experience sampling to link software repositories with emotions and work well-being

Background: The experience sampling method studies everyday experiences of humans in natural environments. In psychology it has been used to study the relationships between work well-being and productivity. To our best knowledge, daily experience sampling has not been previously used in software engineering. Aims: Our aim is to identify links between software developers self-reported affective states and work well-being and measures obtained from software repositories. Method: We perform an experience sampling study in a software company for a period of eight months, we use logistic regression to link the well-being measures with development activities, i.e. number of commits and chat messages. Results: We find several significant relationships between questionnaire variables and software repository variables. To our surprise relationship between hurry and number of commits is negative, meaning more perceived hurry is linked with a smaller number of commits. We also find a negative relationship between social interaction and hindered work well-being. Conclusions: The negative link between commits and hurry is counter-intuitive and goes against previous lab-experiments in software engineering that show increased efficiency under time pressure. Overall, our is an initial step in using experience sampling in software engineering and validating theories on work well-being from other fields in the domain of software engineering.