scholarly journals Mood State and Behavior Predictions in Social Media through Unstructured Data Analysis

2019 ◽  
pp. 1-9
Author(s):  
Gurpreet Singh Bawa ◽  
Suresh Kumar Sharma ◽  
Kanchan K. Jain
Keyword(s):  
Social Media ◽  
Data Analysis ◽  
Personality Trait ◽  
Mood State ◽  
Dirichlet Distribution ◽  
Probability Model ◽  
Unstructured Data ◽  
Latent Features ◽  
The Individual ◽  
And Behavior

For mood State and Behavior Predictions in Social Media through Unstructured Data Analysis, a new model, Behavior Dirichlet Probability Model (BDPM), which can capture the Behavior and Mood of user on Social media is proposed using Dirichlet distribution. There is a colossal amount of data being generated regularly on social media in the form of text from various channels by individuals in the form of posts, tweets, status, comments, blogs, reviews etc. Most of it belongs to some conversation where real-world individuals discuss, analyze, comment, exchange information. Deriving personality traits from textual data can be useful in observing the underlying attributes of the author’s personality which might explain a lot about their behavior, traits etc. These insights of the individual can be utilized to obtain a clear picture of their personality and accordingly a variety of services, utilities would follow automatically. Using Dirichlet probability distribution, the aim is to estimate the probability of each personality trait (or mood state) for an author and then model the latent features in the text which are not captured by the BDPM. As a result, the study can be helpful in prediction of mood state/personality trait as well as capturing the significance of the latent features apart from the ones present in the taxonomies, which will help in making an improved mood state or personality prediction.

scholarly journals The Role of Corporate Social Responsibility in Restoring Green Concepts: Qataris Response to Social Media Campaigns

2020 ◽  
Author(s):  
Rana Hassan
Keyword(s):  
Social Media ◽  
New Media ◽  
Social Responsibility ◽  
Media Technology ◽  
Media Campaigns ◽  
Awareness Campaigns ◽  
The Individual ◽  
Corporate Social ◽  
And Behavior

This research focuses on consumer behavior in Qatar and the individual social responsibility in support of environment. The research also describes the role of social media and CSR in promoting awareness campaigns and how effective they are in changing conceptions and behavior. This is measured by focusing on standards, emotions and actions of individuals and how they are affected by CSR campaigns launched by corporations and public sectors.The study measures the uses and impact of new media technology such as mobile applications and social media in achieving the environment pillar of Qatar vision 2030 in addition to designing effective CSR campaign. The Trans theoretical Model of behavior change, by Prochaska and DiClemente (1983) will be examined through a quantitative analysis on social media users.

The Impact of Big Data on Security

Big Data ◽  
2016 ◽  
pp. 1495-1518
Author(s):  
Mohammad Alaa Hussain Al-Hamami
Keyword(s):  
Social Media ◽  
Big Data ◽  
Management System ◽  
Database Management ◽  
Database Systems ◽  
Structured Data ◽  
Database Management System ◽  
Unstructured Data ◽  
And Behavior ◽  
The Impact

Big Data is comprised systems, to remain competitive by techniques emerging due to Big Data. Big Data includes structured data, semi-structured and unstructured. Structured data are those data formatted for use in a database management system. Semi-structured and unstructured data include all types of unformatted data including multimedia and social media content. Among practitioners and applied researchers, the reaction to data available through blogs, Twitter, Facebook, or other social media can be described as a “data rush” promising new insights about consumers' choices and behavior and many other issues. In the past Big Data has been used just by very large organizations, governments and large enterprises that have the ability to create its own infrastructure for hosting and mining large amounts of data. This chapter will show the requirements for the Big Data environments to be protected using the same rigorous security strategies applied to traditional database systems.

scholarly journals NeuMapper: A scalable computational framework for multiscale exploration of the brain’s dynamical organization

2022 ◽  
pp. 1-154
Author(s):  
Caleb Geniesse ◽  
Samir Chowdhury ◽  
Manish Saggar
Keyword(s):  
Data Analysis ◽  
Dimensionality Reduction ◽  
Topological Data Analysis ◽  
Computational Framework ◽  
Individual Level ◽  
Computational Costs ◽  
Neuroimaging Data ◽  
The Individual ◽  
And Behavior ◽  
Human Neuroimaging

Abstract For better translational outcomes researchers and clinicians alike demand novel tools to distil complex neuroimaging data into simple yet behaviorally relevant representations at the single-participant level. Recently, the Mapper approach from topological data analysis (TDA) has been successfully applied on noninvasive human neuroimaging data to characterize the entire dynamical landscape of whole-brain configurations at the individual level without requiring any spatiotemporal averaging at the outset. Despite promising results, initial applications of Mapper to neuroimaging data were constrained by (1) the need for dimensionality reduction, and (2) lack of a biologically grounded heuristic for efficiently exploring the vast parameter space. Here, we present a novel computational framework for Mapper—designed specifically for neuroimaging data—that removes limitations and reduces computational costs associated with dimensionality reduction and parameter exploration. We also introduce new meta-analytic approaches to better anchor Mapper-generated representations to neuroanatomy and behavior. Our new NeuMapper framework was developed and validated using multiple fMRI datasets where participants engaged in continuous multitask experiments that mimic “ongoing” cognition. Looking forward, we hope our framework could help researchers push the boundaries of psychiatric neuroimaging towards generating insights at the single-participant level while scaling across consortium-size datasets.

scholarly journals Gender Estimation on Social Media Using Recurrent Neural Network

2021 ◽  
Vol 10 (3) ◽  
pp. 1802-1812
Keyword(s):  
Social Media ◽  
Instant Messaging ◽  
Focal Point ◽  
Text Messages ◽  
Unstructured Data ◽  
Gender Orientation ◽  
Grouping Strategies ◽  
Application Programming ◽  
The Individual ◽  
Programming Interfaces

With the development of instant messaging innovation and social media, protection has turned into a significant issue. There is a danger of one’s record being hacked and utilized by the unknown person unconsciously. While doing texting on social media many people use abbreviations, short messages, emojis, images. We tried with different methods to gain the best accuracy in this research. In this paper, we will attempt to check the personality of the individual based on his/her composing style. We will explore the possibility of predicting the gender of a writer utilizing semantic proof. For this reason, term and style-based grouping strategies are assessed over an enormous accumulation of text messages. This study depicts the development of a huge, multilingual dataset named with gender, and examines factual models for deciding the gender of unknown Twitter clients. Twitter gives a basic method to clients to express sentiments, thoughts and assessments, makes the client produced content and related metadata, accessible to the network, and gives simple to utilize web and application programming interfaces to get to the information. The fundamental focal point of this paper is to gather the gender orientation of the client from unstructured data, including the username, screen name, depiction and picture, or by the client produced content

scholarly journals Twitter Data Analysis using R

2019 ◽  
Vol 8 (4) ◽  
pp. 9159-9162
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Public Opinion ◽  
Data Analysis ◽  
Real Life ◽  
Unstructured Data ◽  
Video Images ◽  
Twitter Data ◽  
Wide Perspective ◽  
Twitter Data Analysis

Big Data is an emerging concept in the field of Data mining. It has numerous applications in real life. Most data are coming from social media networking Websites comprising of structured and unstructured data including Text, video, images etc. The main characteristics can be understood by five v’s. Twitter is one among the major evolving social media. Twitter Data analysis can be give you a wide perspective of public opinion regarding any product, public opinion etc which can be used to mine the knowledge from the data. For example, prediction analysis, product review, favourite among people tweets about GST (Goods and service tax).

The Impact of Big Data on Security

2015 ◽  
pp. 276-298 ◽  
Author(s):  
Mohammad Alaa Hussain Al-Hamami
Keyword(s):  
Social Media ◽  
Big Data ◽  
Management System ◽  
Database Management ◽  
Database Systems ◽  
Structured Data ◽  
Database Management System ◽  
Unstructured Data ◽  
And Behavior ◽  
The Impact

Big Data is comprised systems, to remain competitive by techniques emerging due to Big Data. Big Data includes structured data, semi-structured and unstructured. Structured data are those data formatted for use in a database management system. Semi-structured and unstructured data include all types of unformatted data including multimedia and social media content. Among practitioners and applied researchers, the reaction to data available through blogs, Twitter, Facebook, or other social media can be described as a “data rush” promising new insights about consumers' choices and behavior and many other issues. In the past Big Data has been used just by very large organizations, governments and large enterprises that have the ability to create its own infrastructure for hosting and mining large amounts of data. This chapter will show the requirements for the Big Data environments to be protected using the same rigorous security strategies applied to traditional database systems.

Influence of Privacy Fatigue of Social Media Users on Their Privacy Protection Disengagement Behaviour—A PSM based Analysis

2021 ◽  
pp. 1-15
Author(s):  
Xiaojuan Zhang ◽  
Xinluan Tian ◽  
Yuxin Han
Keyword(s):  
Social Media ◽  
Data Analysis ◽  
Propensity Score ◽  
Causal Relationship ◽  
Privacy Protection ◽  
Prediction Accuracy ◽  
Individual Characteristic ◽  
Privacy Issue ◽  
Heterogeneous Effects ◽  
The Individual

This paper aims to examine the net effect of privacy fatigue of social media users on privacy protection disengagement behaviour, which is helpful to address the users’ privacy issue in the new stage of social media digitalization. Applying the Propensity Score Matching(PSM) methodology, the authors conduct the data analysis of 1,734 samples of social media users and eliminates the selectivity error caused by individual characteristic variables so as to improve the prediction accuracy of variable causality. Their research not only validates the causal relationship between privacy fatigue and privacy protection disengagement, proving that privacy fatigue can directly lead to privacy protection disengagement behaviour but also reveals that the individual characteristic variables have heterogeneous effects on the influence of privacy fatigue on protection disengagement behaviour.

PERSEPSI PETERNAK PADA KEPEMIMPINAN PENDAMPING DAN HUBUNGANNYA DENGAN PRODUKTIVITAS USAHA TERNAK DI PAGUYUBAN AL-AWWALIYAH, PASIRWANGI, GARUT, JAWA BARAT

2019 ◽  
Vol 12 (1) ◽  
pp. 42-51
Author(s):  
Dwi Indah Sulistiani ◽  
Ujang Maman ◽  
Junaidi J
Keyword(s):  
Data Analysis ◽  
Secondary Data ◽  
Primary Data ◽  
Leadership Qualities ◽  
Chi Square ◽  
Education Experience ◽  
Spss Software ◽  
Chi Square Analysis ◽  
And Behavior ◽  
The Relationship

Objective of this research; 1) determine the perception of ranchers against the properties and behavior of the leadership of the companion in the Society of Al-Awwaliyah 2) analyze the relationship between productivity breeder with productivity of livestock in the Society of Al-Awwaliyah 3) identify the relationship perceptions of ranchers against the leadership companion with productivity of livestock in the Society of Al-Awwaliyah , The data used in this study are primary and secondary data. Primary data were obtained from questionnaires which stem from ranchers while secondary data sourced from literature in the form of books and articles. Data processing was performed using Chi-square analysis using SPSS software version 21. One of the factors relating to the productivity of ranchers is the perception of ranchers against the leadership of their companion. Leadership companion views of the nature and behavior of which is owned by a companion. Productivity ranchers indirectly related to the productivity of the cattle business. Characteristics breeder visits of age, years of education, experience ranchers, and businesses in addition to ranchers. The results of data analysis showed that there is a significant relationship between business other than ranchers with ranchers productivity. The relationship between the perception of the nature of the companion breeder with productivity ranchers produce Pearson Chi-Square value is 9.751 and Asymp. Sig. (2-sided) of 0.002. This is due to interest ranchers against leadership qualities possessed by a companion who produce prolific ranchers. Ranchers consider that a companion of his leadership qualities are ideal as a companion.

Peranan media sosial dalam pengembangan melek politik mahasiswa

2017 ◽  
Vol 14 (2) ◽  
pp. 139-145
Author(s):  
Yudha Pradana
Keyword(s):  
Social Media ◽  
Data Analysis ◽  
Likert Scale ◽  
Study Habits ◽  
Quantitative Approach ◽  
Result Show ◽  
Political Literacy ◽  
Descriptive Method

This research is used quantitative approach and descriptive method. Instrument used by the research is skala Survey of Study Habits and Attitudes questionnaire to describing media social using by students and Likert Scale questionnaire to describing student’s political literacy. Data analysis using Rank Spearman Order.The result show that social media used by students 48% good, 26% fair, and 15% poor. Student’s political literacy are 36% good, 43% fair, and 21% poor. The role of social media in the development of student's political literacy is 54,79% affected by social media, and 45,21% affected by other factors.

Wykorzystanie mediów społecznościowych w komunikacji z klientem na przykładzie firm sektora piwowarskiego

2015 ◽  
pp. 161-176 ◽  
Author(s):  
Piotr Szamrowski ◽  
Adam Pawlewicz
Keyword(s):  
Social Media ◽  
Public Relations ◽  
Small Enterprises ◽  
Brewing Industry ◽  
Video Sharing ◽  
Advantages And Disadvantages ◽  
Media Platform ◽  
The Individual ◽  
Media Channels ◽  
Regional Character

The main objective of this paper is to identify the platforms and social media tools utilized by the brewing industry in communication with the stakeholders, mainly with potential clients. In addition, the study sought to determine the nature of the published content, identify those responsible for their management, and present the advantages and disadvantages of their conduct in communication and creating the image of the company. The results indicate that only 25% of the surveyed companies do not use social media in PR. This applies only to small enterprises, with regional character. All the major brewing companies in their public relations activities use at least one type of social media, focusing in most cases on social networking (Facebook) and Video Sharing (YouTube). In addition, some of the largest brands included in the individual equity groups have their own social media channels used to communicate with the stakeholders. General promotion of company products and, what is very important, creating a dialogue with social media platform community, were seen as the most important benefits of using social media.

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