Phoey Lee Teh

A concept to measure social capital in social network sites

This paper describes a concept to measure social capital. The concept needs dimensions and illustrative factors to explain the existence of social capital in social network sites. This paper describes the dimensions and factors to measure social capital. The objective of this paper is to demonstrate a way to describe social capital. The description of social capital supports the measurement and gives the scientific world the opportunity to identify and to attest social capital in social network sites. The value of the paper is the concept to measure social capital with a questionnaire and gives the opportunity to identify social capital in networks with many participants.

Reversing the polarity with emoticons

Technology advancement in social media software allows users to include elements of visual communication in textual settings. Emoticons are widely used as visual representations of emotion and body expressions. However, the assignment of values to the “emoticons” in current sentiment analysis tools is still at a very early stage. This paper presents our experiments in which we study the impact of positive and negative emoticons on the classifications by fifteen different sentiment tools. The “smiley” :) and the “sad” emoticon :( and raw-text are compared to verify the degrees of sentiment polarity levels. Questionnaires were used to collect human ratings of the positive and negative values of a set of sample comments that end with these emoticons. Our results show that emoticons used in sentences are able to reverse the polarity of their true sentiment values.

Use of Social Network Site´s Profile for the Employment Seeking Process

This paper investigates the use of social network site´s profile to present individuals to potential employers. Prestige is an important issue of social capital theory, social network sites members present their knowledge and skills to other members to have a benefit. The results of the survey of 440 people about their behaviour for the employment seeking process on social network sites are presented. The paper provides the analysis of reasons to present themselves in social network sites and defines the risks for organisations who use social network site´s profile to evaluate candidates. The purpose of the paper is to evaluate and explain the behaviour of individuals on social network sites for the employment seeking process and to test if the theoretical mechanism of the social capital theory can explain the operation of social network sites.

The Intention to Share and Re-Shared among the Young Adults towards a Posting at Social Networking Sites

The activity of sharing information among the young adults over the Internet has led to various types of damages in the community. This study explores the damages leading from posting of young adults’ overs the social network. The damages in this context refer to the damages in the form of business reputation, psychologist damages, cyber bullying and etc. In order to provide a neutralizing platform to these damages, the intention on the sharing and re-sharing between the postings among the young adults is studied. This paper summarizes the result of the intention to share and re-shared mechanism of the young adults on a posting at social networking sites.

Your social network profile reveals you

Purpose This study aims to evaluate the fears of individuals on their profiles’ sharing in social network sites (SNSs), regarding its advantages and disadvantages. The researched issues are related with the employment seeking process. The concern of this study is the deviation observation between the fears acquired by the business and private social media members. Design/methodology/approach This study included an online survey with 236 respondents and calculated indicators of central tendency or location parameter, correlation coefficients and performed analysis of variance. Findings The result indicated and revealed the hidden danger and opportunities among social network members’ profile. This result addressed the need to consider the issue of user’s fears in reengineering the practical use of SNSs by organisations. Research limitations/implications Interesting for further research would be to transfer this research from the employment seeking process in other research fields to generalise the results more accurately. Originality/value The contribution to the research field is to compare different SNSs and to explain the reasons to use SNS profiles to support organisations by their decisions for a valuable strategy. This study provides an insight in use and behaviour of SNS members that support researchers to understand the behaviour of SNS members regarding their profile under consideration of the employment seeking process.

Text Segmentation Techniques: A Critical Review

Text segmentation is a method of splitting a document into smaller parts, which is usually called segments. It is widely used in text processing. Each segment has its relevant meaning. Those segments categorized as word, sentence, topic, phrase or any information unit depending on the task of the text analysis. This study presents various reasons of usage of text segmentation for different analyzing approaches. We categorized the types of documents and languages used. The main contribution of this study includes a summarization of 50 research papers and an illustration of past decade (January 2007−January 2017)’s of research that applied text segmentation as their main approach for analysing text. Results revealed the popularity of using text segmentation in analysing different languages. Besides that, the word segment seems to be the most practical and usable segment, as it is the smaller unit than the phrase, sentence or line.

Identifying and Categorising Profane Words in Hate Speech

This study attempts to explore the different types of Hate Speech appearing in social media by identifying profane words used in hate speech. This study also compares the profane words used in different generations to assist in identifying the users profile. Five-hundred (500) comments posted on YouTube on the abusive topics were collected. Profane words are classified into eight different types of hate speech. The finding shows 35% of profane words found in our sample are words related to sexual orientation. Comparison of the terms between 1970 and 2017 also show a high percentage of profane words are sexual orientation. Though the results are found based on only 500 comments collected from YouTube link in the current study, they are useful in establishing the list of profane words which will serve as the base for automatic hate speech identification in our future study. The originality of this research is the development of a training list of profane words for each category and comparison of the type of the words used in 1970 century with todays social media platform.