The success of any task relies on the efforts made by a person, but it cannot be achieved without the cooperation of other persons who are being helpful. So, we would like to thank Government Engineering Collage, Modasa and Computer Engineering for giving us the opportunity of doing this project.
The entire session of our phase I completion was a great experience providing us with the insight & invocation into learning various software engineering concepts & benefits of teamwork. We would like to take this opportunity to express our sincere thanks to all those people without whose support and cooperation, it would have been difficult to complete this project.
Primarily, we are very much thankful to our project guide Mr. Nilesh Narendra Maltare for his leading guidance and sincere efforts throughout project work. He took a deep interest in simplifying the difficulties. Also, he has been a consistent source of inspiration for us.
Sentiment is an attitude, thought, or judgment prompted by feeling.
Sentiment analysis, which is also known as opinion mining, studies people’s sentiments towards certain entities. Internet is a resourceful place with respect to sentiment itformation. From a user’s perspective, people are able to post their own content through various social media, such as fotums, micro-blogs, or online social networking sites. From a researcher’s perspective, many social media sites release their application programming interfaces (APIs), prompting data collection and analysis by researchers and developers. For instance, Twitter currently has three different versions of APIs available, namely the REST API, the Search API, and the Streaming API.
With the REST API, developers are able to gather status data and user information; the Search API allows developers to query specific Twitter content, whereas the Streaming API is able to collect Twitter content in real time. Moreover, developers can mix those APIs to create their own applications. Hence, sentiment analysis seems having a strong fundament with the support of massive online data.
The main purpose of our system is as follows:
HTML 5 is a markup language used for structuring and presenting content on the World Wide Web. It is the fifth and current major version of the HTML standard and subsumes XHTML. It currently exists in two standardized forms: HTML 5.2 Recommendation by the World Wide Web Consortium (W3C, a broad coalition of organizations), intended primarily for Web content developers; and HTML Living Standard by WHATWG (a small consortium of four browser vendors), intended primarily for browser developers, though it also exists in an abridged Web developer version. There are minor conflicts between the two groups’ specifications. HTML 5 was first released in a public-facing form on 22 January 2008, with a major update and “W3C Recommendation” status in October 2014. Its goals are to improve the language with support for the latest multimedia and other new features; to keep the language both easily readable by humans and consistently understood by computers and devices such as Web browsers, parsers, etc., without XHTML’s rigidity; and to remain backward-compatible with older software. HTML 5 is intended to subsume not only HTML 4, but also XHTML 1 and DOM Level 2 HTML; the HTML 4 and XHTML specs were announced as superseded by HTML 5.2 on 27 March 2018.
Spring Boot is an open source Java-based framework used to create a Micro Service. It is developed by Pivotal Team. Spring Boot contains a comprehensive infrastructure support for developing a micro service and enables you to develop enterprise-ready applications that you can “just run”.
Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Python’s simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse.
Java is a general-purpose programming language that is class-based, object-oriented, and designed to have as few implementation dependencies as possible.
MongoDB is a cross-platform document-oriented database program. Classified as a NoSQL database program, MongoDB uses JSON-like documents with schema. MongoDB is developed by MongoDB Inc. and licensed under the Server Side Public License.
Spiral Model – A Combination of Iterative and Waterfall Models:
Tagged as a union of the waterfall and iterative models, the Spiral Model begins with a small set of requirements which are compared at every stage of software development to ensure their perfect matching. Every phase of a spiral model is initiated according to the design goal of your client, ending with a client review.
The word Spiral is apt for this model as the team of software developers working on a project add functionalities to the requirements in the pattern of broadening spirals till such time the entire application is ready to move on to the production phase.
Apt for large and medium-risk projects, a spiral model can be employed to projects which demand frequent releases. Best suited to projects which have vague or complex specifications, this model helps developers make changes to the code at any point in time.
The Spiral Model comprises of four stages: –
Criteria for Selecting Software Process Models:
There are two groups of users using the system:
Admin installs our whole system and maintains the server so that the system works properly.
Uses filters and search facility to fetch the tweets and uses the sentiment analysis feature to get a brief about the sentiments in tweets , also graphs and charts are provided with some examples.
The current Review analyzing is quite infeasible , inefficient and very expensive . Each and every review is to be read and understood which can take months on a big data set . There are some tweet analysis apps out there which are not as realible and accurate because they don’t have feedback system and only use one source of operation.
The feasibility study is an important step in any software development process. This is because it makes an analysis of different aspects like cost required for developing and executing the system, the time required for each phase of the system and so on.
The preliminary investigation examines project feasibility, the likelihood the system will be useful to the organization. The main objective of the feasibility study is to test the Technical, Operational and Economical feasibility for adding new modules and debugging old running systems. All system is feasible if they are unlimited resources and infinite time. There are aspects in the feasibility study portion of the preliminary investigation:
The technical issue usually raised during the feasibility stage of the investigation includes the following:
Proposed projects are beneficial only if they can be turned out into an information system. That will meet the organization’s operating requirements. Operational feasibility aspects of the project are to be taken as an important part of the project implementation. Some of the important issues raised are to test the operational feasibility of a project includes the following: –
A system can be developed technically and that will be used if installed must still be a good investment for the organization. In the economic feasibility, the development cost in creating the system is evaluated against the ultimate benefit derived from the new systems.
The empathy map was created as a tool to help you gain an understanding of a targeted persona. Thus, you can use it when you want to deliver a better user experience of your product/service. In the process, the exercise can also help you identify the things you don’t know about your users yet so you can carry out new research to fill in those gaps.
AEIOU is a heuristic to help interpret observations gathered by ethnographic practice in the industry. Its two primary functions are to code data, and to develop building blocks of models that will ultimately address the objectives and issues of a client.
Within the Ideation phase, we select a test case where we have more have emotional attachment and solutions for the problem faced by the people in the selected test case are considered further.
The purpose of this service is to design and implement a good and efficient service for RTO.
After the idea is implemented it will be easier to analyse tweets in bulk and visualize the sentiments with graphs and charts, it also provides reliability and accuracy as multiple libraries are used and also has a feedback section for wrongly analysed tweets.
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