Predicting dark triad personality traits from twitter usage and a linguistic analysis of tweets in python

 Predicting dark triad personality traits from twitter usage and a linguistic analysis of tweets

 PROJECT ID: PYTHON20

 

PROJECT NAME: Predicting dark triad personality traits from twitter usage and a linguistic analysis of tweets

 

PROJECT CATEGORY: MCA / BCA / BCCA / MCM / POLY / ENGINEERING

 

PROJECT ABSTRACT:

Social media sites are now the most populardestination for Internet users, providing social scientists with agreat opportunity to understand online behaviour. There are agrowing number of research papers related to social media, asmall number of which focus on personality prediction. To date,studies have typically focused on the Big Five traits ofpersonality, but one area which is relatively unexplored is that ofthe anti-social traits of narcissism, Machiavellianism andpsychopathy, commonly referred to as the Dark Triad. Thisstudy explored the extent to which it is possible to determine anti-social personality traits based on Twitter use. This wasperformed by comparing the Dark Triad and Big Fivepersonality traits of 2,927 Twitter users with their profileattributes and use of language. Analysis shows that there aresome statistically significant relationships between thesevariables. Through the use of crowd sourced machine   earning algorithms, we show that machine learning provides usefulprediction rates, but is imperfect in predicting an individual’s Dark Triad traits from Twitter activity. While predictive models may be unsuitable for predicting an individual’s personality, they may still be of practical importance when models are applied tolarge groups of people, such as gaining the ability to see whetheranti-social traits are increasing or decreasing over a population.Our results raise important questions related to the unregulateduse of social media analysis for screening purposes. It isimportant that the practical and ethical implications of drawingconclusions about personal information embedded in socialmedia sites are better understood

SOFTWARE REQUIREMENTS:

OS                                : Windows

Python IDE                  : Python 2.7.x and above

Language                             : Python Programming

Database                             : MYSQL

 

HARDWARE REQUIREMENTS:

 RAM                :  4GB and Higher

Processor          :  Intel i3 and above

Hard Disk         : 500GB Minimum

 

Conclusion

This study highlights that there are relationships betweenTwitter activity, Dark Triad and Big Five personality traits,but that the practical performance of machine prediction iscurrently poor when applied directly to an individual. Ourresults demonstrate that while our models display a highdegree of accuracy, defined as (TP + TN) / (TP + TN + FP +FN); the TPR and TNR remain poor, highlighting a need forgreater focus on evaluation criteria in future studies.As research in this field matures, behavioural researchwith social media will likely offer an important insight intothe levels and variability of anti-social behaviours within andbetween social groups. While mainstream media reports mayfocus on individual level personality prediction, this field ofresearch may be of greater use in examining changes insociety over time.Results also indicate that while users may be careful aboutthe content they post on Twitter, the words they use mayreveal more about their personalities than they would wish.This points to critical questions around the possible need forregulatory controls and/or raising awareness amongst users inorder to prevent the misuse of information derived fromTwitter and other online social network activity

 

TABLE OF CONTENTS

·        Title Page      

·        Declaration

·        Certification Page

·        Dedication

·        Acknowledgements

·        Table of Contents

·        List of Tables

·        Abstract

 

CHAPTER SCHEME

CHAPTER ONE: INTRODUCTION

CHAPTER TWO: OBJECTIVES

CHAPTER THREE: PRELIMINARY SYSTEM ANALYSIS

·         Preliminary Investigation

·         Present System in Use

·         Flaws In Present System

·         Need Of New System

·         Feasibility Study

·         Project  Category

CHAPTER FOUR: SOFTWARE ENGINEERING AND PARADIGM APPLIED   

·         Modules

·         System / Module Chart

CHAPTER FIVE: SOFTWARE AND HARDWARE REQUIREMENT

CHAPTER SIX: DETAIL SYSTEM ANALYSIS

·         Data Flow Diagram

·         Number of modules and Process Logic

·         Data Structures  and Tables

·         Entity- Relationship Diagram

·         System Design

·         Form Design 

·         Source Code

·         Input Screen and Output Screen

CHAPTER SEVEN: TESTING AND VALIDATION CHECK

CHAPTER EIGHT: SYSTEM SECURITY MEASURES

CHAPTER NINE: IMPLEMENTATION, EVALUATION & MAINTENANCE

CHAPTER TEN: FUTURE SCOPE OF THE PROJECT

CHAPTER ELEVEN: SUGGESTION AND CONCLUSION

CHAPTER TWELE: BIBLIOGRAPHY& REFERENCES          

Other Information

 

PROJECT SOFWARE	ZIP
PROJECT REPORT PAGE	60 -80 Pages
CAN BE USED IN	Marketing (MBA)
PROJECT COST	1500/- Only
PDF SYNOPSIS COST	250/- Only
PPT PROJECT COST	300/- Only
PROJECT WITH SPIRAL BINDING	1750/- Only
PROJECT WITH HARD BINDING	1850/- Only
TOTAL COST (SYNOPSIS, SOFTCOPY, HARDBOOK, and SOFTWARE, PPT)	2500/- Only
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