Academic literature on the topic 'Polarity Analysis Software'

A lot of user-generated data is available these days from huge platforms, blogs, websites, and other review sites. These data are usually unstructured. Analyzing sentiments from these data automatically is considered an important challenge. Several machine learning algorithms are implemented to check the opinions from large data sets. A lot of research has been undergone in understanding machine learning approaches to analyze sentiments. Machine learning mainly depends on the data required for model building, and hence, suitable feature exactions techniques also need to be carried. In this chapter, several deep learning approaches, its challenges, and future issues will be addressed. Deep learning techniques are considered important in predicting the sentiments of users. This chapter aims to analyze the deep-learning techniques for predicting sentiments and understanding the importance of several approaches for mining opinions and determining sentiment polarity.

This chapter combines disruptive innovation strategy (DIS) theory with the system dynamics (SD) modeling method. It presents a simulation model of the hard-disk (HD) maker population overshoot and collapse dynamics, showing that DIS can crucially affect the dynamics of the IT industry. Data from the HD maker industry help calibrate the parameters of the SD model and replicate the HD makers’ overshoot and collapse dynamics, which DIS allegedly caused from 1973 through 1993. SD model analysis entails articulating exactly how the structure of feedback relations among variables in a system determines its performance through time. The HD maker population model analysis shows that, over five distinct time phases, four different feedback loops might have been most prominent in generating the HD maker population dynamics. The chapter shows the benefits of using SD modeling software, such as iThink®, and SD model analysis software, such as Digest®. The latter helps detect exactly how changes in loop polarity and prominence determine system performance through time. Strategic scenarios computed with the model also show the relevance of using SD for information system management and research in areas where dynamic complexity rules.

In India, IT (Information technology) and ITeS industry is divided into four major segments – a) IT services, b)Business Process Management (BPM), c) Software Products and Engineering Services, and d) Hardware. Chennai is the one of the largest information technology service providers in India. This sector in Chennai provides employment for many technical and non-technical graduates professionally. The leading companies provide high monetary and non-monetary benefits for their employees. The leading IT companies in Chennai are 1) Infosis, 2) TCS, 3) HCL, 4) WIPRO, 5) IBM, 6) HP, 7) HP, 8) DELL, 9) POLARIS etc. Work Life balance means the healthy balance between the professional life and personal life. The samples for this research study are collected by adopting stratified random sampling and random sampling methods. The samples are collected from the four regions (North, South, East and West) proportionately. The questionnaires were circulated among different age groups. The Sample size is 500.The data is analysed by using simple statistical tools like a. Percentage Analysis, b. Average Analysis, c. Chi -Square Method, d. One way ANOVA. From the study it is concluded that, there is the impact of Experience, Marital Status and educational qualification on work-life balance. Some of the most contributing factors in work life balance area. Salary, b. Location of work place, c. Holidays, d. Interest in Job, e. Career development opportunities, f. Leave arrangements, g. Flexible working hours, h. Training opportunities, i. Job security, j. Friendly environment. Among the leave benefit ‘Maternity leave ranked the first, followed by other leave benefits like paternity leave, sick leave, sabbatical leave and bereavement leave. Flexible work time, work-from home and work from anywhere are the options provided by many organizations to improve the employee morale and to sustain the employees. Lot of employees are happy with these systems