FILTERING POLITICAL SENTIMENT IN SOCIAL MEDIA FROM TEXTUAL INFORMATION
ABSTRACT
The Filtering Political Sentiment in Social Media from Textual Information system is capable of filtering the political hazardous sentiments using text mining and web mining techniques. The aim of the study is to design and implement a system that will Filter Political Sentiment in Social Media from Textual Information. In achieving this aim, the following specific objectives were laid out to implement a program where a social media post or comment written in English language as an input to classify its sentiment either political or nonpolitical, detect and prevent the malicious political sentiments or comments from Facebook post which plays a important role in influencing the people’s and societies sentiments, and understand sentiment of any social media post this method can be used. The motivation led towards embarking on this research work is the problems encountered in the existing system which entails the malicious political sentiments or comments from Facebook post which plays a important role in influencing the people’s and societies sentiments, the researcher proposed the filtering the political sentiments of by using textual information. The methodology adopted in this study is the structured system analysis and design methodology (SSADM) which is a technical approach for analyzing and designing an application or system by applying object throughout the software development process. The programming language used is HTML, CSS, JAVASCRIPT, PHP, SQL and JQUERY. The reason why web programming languages was used is because, it is platform independent and it is a web based application. The results of this study will throw light on approaches to Filtering Political Sentiment in Social Media from Textual Information and how it can be used as a tool for national development. This project will be of benefit to: Enterprises, Political Parties and subsequent researchers. The expected result is an electronic system that will Filter Political Sentiment in Social Media from Textual Information and the system will generates an accurate information for decision making purpose.
CHAPTER ONE
1.1 Introduction
The Filtering Political Sentiment in Social Media from Textual Information system is capable of filtering the political hazardous sentiments using text mining and web mining techniques. To understand sentiment of any social media post this method can be used. This can be used to create peaceful society by reducing political turbulence. The classification depends on dictionary that we provided and training to the words. Due to the rapid growth of the Internet, the networked population has been increasing to a few billions (Elif et al., 2014). As a result, social media plays a vital role in the life of civil society worldwide and people are gaining greater access to information, more opportunities to engage themselves in handling public opinions and an enhanced ability to undertake collective action. As a prelude to other parts of this study, this chapter will discuss the background upon which this study was initiated, the statement of problems that led to this study, the Aim and Objectives of the study. Others are Significance of the study, Scope of work, Limitations of the Study and Definition of technical terms.
1.2 Background of Study
The early days of social networking sites were viewed merely for friendship or dating purposes. But, with the progress of time the characteristics of most of the social media are now changing. For example, in 2008 and 2012 US presidential elections, social media were used for election campaign and for the engagement of the youth (Kristin, 2011). Again in 2009, social media - twitter was used efficiently by the politically interested people and the politicians during German general election to conduct the election campaign and to discuss political events (Pascal, 2011). Nowadays social media is playing a important role in affecting people’s feelings in side or opposite a government or an institution. Therefore, to understand the sentiment of any posting in social media, an effective procedure is necessity. Some Facebook postings were analyzed to understand political sentiments. In any politically infected posting, there are some dominant words.
At beginning, we have created a dictionary consisting of unique words gathered from political or nonpolitical posts or comments and then trained using Naïve Bayes algorithm based on probability algorithm. To identify the sentiment expressed in a new post or comment, we have taken each word of the posting and then compared those with the dictionary words for classification. At last, we have tested our algorithm using two hundred postings from Facebook and our result shows that the method can classify posts or comments with good accuracy.
A lot of political gurus, academics and journalists have embraced social media as an undeniable force for good, claiming that democracy is just a tweet away. Moreover, political specialists believe that if people want to liberate a society, they need to use Internet in a proper way. Internet has been heralded as an effective weapon of the weak people against their authoritarian leaders. It is now an ongoing phenomenon that on one side government thugs firing bullet and on the other side.
1.3 Statement of Problems
Investigation revealed the problems of the Filtering Political Sentiment in Social Media from Textual Information existing system which entails the malicious political sentiments or comments from Facebook post which plays a important role in influencing the people’s and societies sentiments, the researcher proposed the filtering the political sentiments of by using textual information. The Researcher will have provided dictionary which will contain words that may hurt someone’s sentiment.
1.4 Aim and Objectives of Study
The aim of the study is to design and implement a system that will Filter Political Sentiment in Social Media from Textual Information. In achieving this aim, the following specific objectives were laid out as follows:
- To implement a program where a social media post or comment written in English language as an input to classify its sentiment either political or nonpolitical.
- To detect and prevent the malicious political sentiments or comments from Facebook post which plays a important role in influencing the people’s and societies sentiments.
- To understand sentiment of any social media post this method can be used.
- To reduce political turbulence and stop prank in social Media.
- To classify posts or comments with good accuracy and maintain peaceful environment in social media.
1.5 Significance of Study
The following are the significance of this study:
- The results of this study will throw light on approaches to Filtering Political Sentiment in Social Media from Textual Information and how it can be used as a tool for national development.
- This research will also serve as a resource base to other scholars and researchers interested in carrying out further research in this field subsequently, if applied will go to an extent to provide new explanation to the topic.
1.6 Scope of Study
The study focuses on the Filtering Political Sentiment in Social Media from Textual Information using Facebook social media platform as a case study.
1.7 Limitations of the Study
During the course of this study, many things militated against its completion, some of which are:
- Time Constraint: The time frame given to accomplish this project was very short due to school academic calendar and it was carried out under pressure which made the researcher not to implement some necessary features.
- Research material: availability of research material is a major setback to the scope of the study.
- Frequent power failure: This made the researcher append more money on fuel to ensure sustainable power.
- Financial Constraint: Insufficient fund tends to impede the efficiency of the researcher in sourcing for the relevant materials, literature or information and in the process of data collection (internet).
1.8 Definition of Terms
Learning Objects: In the context of this research, a learning-object-is-a-resource with a clear educational-application. It is in digital form − examples: a Microsoft Word Document or a PDF document.
Catalog: This research applies the word ‘catalog’ as a container that presents all the SICT projects logged/stored in an organized tabular format, showing relevant information about each project. It can be compared to a library catalog containing all the information about books − their titles, author, number of pages, published year, ISBN etc.
Repository: A repository (in this case; SICT repository) is an archive, storehouse or container that allows storage, cataloging, accessing all SICT undergraduate projects and thesis, and viewing each object’s content.
Identifier: An identifier is simply a unique identity attached to one object, it aids referencing such object directly when its identifier is requested. An identifier can be a serial number, identity number (also written as ‘ID’) or an index number.
Object: An object in the context of this research refers to a project record returned by a database − queried using an Object Oriented Programming (OOP) approach. An object (i.e. a project record) returns or contains the project topic, student name, abstract, year of project submission and the date and time the object record was created.
Database: A database is a repository that allows storage, retrieval and manipulation of data. A database can be used efficiently with the aid of a Database Management System (DBMS) − a set of tools that allow storage, access, retrieval and maintenance of data stored in a database, examples of DBMS include XAMPP, WAMP, LAMP and AppServ to mention a few.
Web-Browser: A web-browser, internet browser or browser is software program that interprets the codes written in markup languages in graphic and visual (like images, text, audio or animation) form. This allows users to easily request and access a website or to search for information through a search engine (either Google, Ask, Bing and AOL among others).
Keyword: A phrase or just one word that is used to search for a certain result or set of results.
User: A user is system, application, request or person that can use a computer or software to perform a specific task.
Metadata: A set of data that describes and gives information about other data.
Dataset: A collection of related game plans of information that is made out of disengaged segments however can be controlled as a unit by a PC.
Relational Database: A database composed to see association among relations of information delineates tables from which data can be gotten to or reassembled in different courses without rearranging the database tables.
CHAPTER TWO
2.0 Literature Review
2.1 Introduction
The review of relevant literature is the main topic of this chapter. A literature review covers theoretical and methodological contributions to a certain issue in addition to the state of knowledge at the time of writing. It provides information about the state of the art in relation to the subject you are writing about. It examines the body of work on the chosen subject. The literature evaluation in this study comprises the …
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TABLE OF CONTENTSPRELIMINARY PAGES
- Title page
- Approval page
- Dedication
- Acknowledgement
- Table of Contents
- Abstract
INTRODUCTION
- 1.1 Introduction
- 1.2 Background of Study
- 1.3 Statement of Problems
- 1.4 Aim and Objectives of Study
- 1.5 Significance of Study
- 1.6 Scope of Study
- 1.7 Limitations of the Study
- 1.8 Definition of Terms
LITERATURE REVIEW
- 2.1 Introduction
- 2.2 Conceptual Review of Social Media
- 2.3 Role and Challenges of Social Media Usage
- 2.4 Information Security Challenges in Social Media
- 2.5 The Concept of Social Media Registration
- 2.5.1 Online Social Media Registration
- 2.5.2 Usage of Online Social Media Registration Forms
- 2.6 Social Media Web Portal
- 2.6.1 Types of Web Portals
- 2.7 Database for Student Web Portals
- 2.7.1 Merits of Integrating Databases in Web Applications
- 2.8 Overview of Information System
SYSTEM ANALYSIS AND DESIGN
- 3.1 Methodology Adopted
- 3.1.1 Problem Identification Using SSADM
- 3.2 Analysis of the Existing System
- 3.2.1 Dataflow of the Existing System
- 3.2.2 Disadvantages Of The Existing System
- 3.2.3 Weakness of the existing System
- 3.3 Analysis of the Proposed System
- 3.3.1 Data Flow Diagram of the Proposed System
- 3.3.2 Advantages of the Proposed System
- 3.3.3 Justification of the Proposed System
- 3.4 Functional Requirements
- 3.4.1 Use Case Diagram Of The Admin / User Privileges
- 3.5 Data Requirements
- 3.6 High Level Model of the Proposed System
SYSTEM DESIGN AND IMPLEMENTATION
- 4.1 Objectives of the Design
- 4.2 Cohesion and Decomposition High level Model
- 4.3 Control Center / Overall Dataflow Diagram
- 4.3.1 Proposed System Operation Flowchart
- 4.4 System Specification and Design
- 4.4.1 Input and Output Specification
- 4.4.2 Database Specification and Design
- 4.4.3 Data Dictionary
- 4.5 Choice and Justification of Programming Language
- 4.6 Program Documentation
- 4.7 Implementation Techniques
- 4.8 Programming Module Specification
- 4.8.1 Installation
- 4.9 Computer Hardware Minimum Requirement
- 4.10 Software Requirement
- 4.11 Personnel / User Training
SUMMARY, CONCLUSION AND RECOMMENDATION
- 5.1 Introduction
- 5.2 Summary
- 5.3 Conclusion
- 5.4 Recommendation
REFERENCES
APPENDIX A - “SOURCE CODE”
APPENDIX B - “OBJECT PROGRAM”
Disclaimer for Complete Material Utilization
The displayed research work titled "Filtering Political Sentiment in Social Media from Textual Information" is stated as a research guideline towards accomplishing your assigned project / seminar research work. All the research materials on this website are ONLY for research purposes and should be used as a guideline in developing your research work. For no reason should you copy word for word as projectlist.com.ng will not be liable for any who copied the material. By ordering the complete research guideline, it signifies that you've accepted our terms of service.
PRELIMINARY PAGES
- Title page
- Approval page
- Dedication
- Acknowledgement
- Table of Contents
- Abstract
INTRODUCTION
- 1.1 Introduction
- 1.2 Background of Study
- 1.3 Statement of Problems
- 1.4 Aim and Objectives of Study
- 1.5 Significance of Study
- 1.6 Scope of Study
- 1.7 Limitations of the Study
- 1.8 Definition of Terms
LITERATURE REVIEW
- 2.1 Introduction
- 2.2 Conceptual Review of Social Media
- 2.3 Role and Challenges of Social Media Usage
- 2.4 Information Security Challenges in Social Media
- 2.5 The Concept of Social Media Registration
- 2.5.1 Online Social Media Registration
- 2.5.2 Usage of Online Social Media Registration Forms
- 2.6 Social Media Web Portal
- 2.6.1 Types of Web Portals
- 2.7 Database for Student Web Portals
- 2.7.1 Merits of Integrating Databases in Web Applications
- 2.8 Overview of Information System
SYSTEM ANALYSIS AND DESIGN
- 3.1 Methodology Adopted
- 3.1.1 Problem Identification Using SSADM
- 3.2 Analysis of the Existing System
- 3.2.1 Dataflow of the Existing System
- 3.2.2 Disadvantages Of The Existing System
- 3.2.3 Weakness of the existing System
- 3.3 Analysis of the Proposed System
- 3.3.1 Data Flow Diagram of the Proposed System
- 3.3.2 Advantages of the Proposed System
- 3.3.3 Justification of the Proposed System
- 3.4 Functional Requirements
- 3.4.1 Use Case Diagram Of The Admin / User Privileges
- 3.5 Data Requirements
- 3.6 High Level Model of the Proposed System
SYSTEM DESIGN AND IMPLEMENTATION
- 4.1 Objectives of the Design
- 4.2 Cohesion and Decomposition High level Model
- 4.3 Control Center / Overall Dataflow Diagram
- 4.3.1 Proposed System Operation Flowchart
- 4.4 System Specification and Design
- 4.4.1 Input and Output Specification
- 4.4.2 Database Specification and Design
- 4.4.3 Data Dictionary
- 4.5 Choice and Justification of Programming Language
- 4.6 Program Documentation
- 4.7 Implementation Techniques
- 4.8 Programming Module Specification
- 4.8.1 Installation
- 4.9 Computer Hardware Minimum Requirement
- 4.10 Software Requirement
- 4.11 Personnel / User Training
SUMMARY, CONCLUSION AND RECOMMENDATION
- 5.1 Introduction
- 5.2 Summary
- 5.3 Conclusion
- 5.4 Recommendation
REFERENCES
APPENDIX A - “SOURCE CODE”
APPENDIX B - “OBJECT PROGRAM”
Disclaimer for Complete Material Utilization
The displayed research work titled "Filtering Political Sentiment in Social Media from Textual Information" is stated as a research guideline towards accomplishing your assigned project / seminar research work. All the research materials on this website are ONLY for research purposes and should be used as a guideline in developing your research work. For no reason should you copy word for word as projectlist.com.ng will not be liable for any who copied the material. By ordering the complete research guideline, it signifies that you've accepted our terms of service.
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