scholarly journals Toxic Word Analyzer

2021 ◽  
pp. 578-581
Author(s):  
Dhairya Timbadia
Keyword(s):  
Social Media ◽  
Huge Amount ◽  
Current Generation ◽  
Stop Word ◽  
Input Sentence

In this generation social media has been a huge part of our lives and there is no need to say that the current generation spend a huge amount of time on their social media accounts. Apart from there being a good social media influencer there are a lot of people who spread hatred among these influencers as well as among each other. I have tried to make a speedometer which would be able to tell the toxicity of the words that are basically used in the input sentence or paragraph. The main processing that would be done on the sentence or the paragraph would be removing punctuation marks, tokenization on the words, ‘Stop’ word removal, bigram creation, matching tokens with predefined dictionary, generating toxicity percent using scaling.

scholarly journals Digital sources: a case study of the analysis of the Recovery of Historical Memory in Spain on the social network Twitter

2019 ◽  
Vol 7 (2) ◽  
pp. 015 ◽  
Author(s):  
Mariluz Congosto
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Social Network ◽  
Historical Memory ◽  
Historical Research ◽  
Huge Amount ◽  
Online Social Media ◽  
The Social ◽  
Special Relevance

The incorporation of digital sources from online social media into historical research brings great opportunities, although it is not without technological challenges. The huge amount of information that can be obtained from these platforms obliges us to resort to the use of quantitative methodologies in which algorithms have special relevance, especially regarding network analysis and data mining. The Recovery of Historical Memory in Spain on the social network Twitter will be analysed in this article. An open-code tool called T-Hoarder was used; it is based on objectivity, transparency and knowledge-sharing. It has been in use since 2012.

Sentiment Analysis with Social Media Analytics, Methods, Process, and Applications

2017 ◽  
pp. 192-208
Author(s):  
Karteek Ramalinga Ponnuru ◽  
Rashik Gupta ◽  
Shrawan Kumar Trivedi
Keyword(s):  
Social Media ◽  
Support Vector Machine ◽  
Sentiment Analysis ◽  
Support Vector ◽  
Social Media Analytics ◽  
Nearest Neighbour ◽  
Huge Amount ◽  
Word Clouds

Firms are turning their eye towards social media analytics to get to know what people are really talking about their firm or their product. With the huge amount of buzz being created online about anything and everything social media has become ‘the' platform of the day to understand what public on a whole are talking about a particular product and the process of converting all the talking into valuable information is called Sentiment Analysis. Sentiment Analysis is a process of identifying and categorizing a piece of text into positive or negative so as to understand the sentiment of the users. This chapter would take the reader through basic sentiment classifiers like building word clouds, commonality clouds, dendrograms and comparison clouds to advanced algorithms like K Nearest Neighbour, Naïve Biased Algorithm and Support Vector Machine.

Does Social Media Really Help?

2016 ◽  
Vol 6 (3) ◽  
pp. 15-33
Author(s):  
Rebecca Liu ◽  
Aysegul Eda Kop
Keyword(s):  
Social Media ◽  
New Product Development ◽  
New Product ◽  
Evaluation Tool ◽  
Huge Amount ◽  
Moderation Effect ◽  
Customer Involvement ◽  
Product Success ◽  
Use Of Social Media ◽  
Critical Literature

This paper intends to understand whether social media helps new product success in the context of customer involvement. The authors present a debate about the opportunities and challenges of using social media in new product development (NPD). Through a critical literature review, a conceptual model with a moderation effect is presented. The review is mainly derived from 286 relevant papers published in top-ranked journals between 2005 and 2014. The results suggest that while social media provides an effective and efficient method for collecting information and knowledge about customers' expectations and experiences, it does not necessarily always lead to NPD success. The study shows that hidden customer needs, an advanced evaluation tool, the huge amount of information and a firm's absorptive capacity challenge the use of social media.

scholarly journals ALGEBRAIC THINKING ABILITY AND LEARNING INTEREST THROUGH SOCIAL MEDIA-BASED PICTORIAL PUZZLE IN NEW NORMAL ERA

MaPan ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 329-342
Author(s):  
Putik Rustika ◽  
◽  
Titi Rohaeti
Keyword(s):  
Social Media ◽  
Learning Process ◽  
Mathematical Thinking ◽  
Algebraic Thinking ◽  
Current Generation ◽  
New Normal ◽  
High Category ◽  
Thinking Ability ◽  
Main Thing ◽  
Learning Interest

Algebraic ability is one of the most important abilities to be developed because it becomes the basis to achieve other mathematical thinking ability. In new normal era, information through social media is the main thing for society, particularly for children of the current generation. This study aims to describe algebraic thinking ability and students' interest in learning through social media-based pictorial puzzles. The method of the research is descriptive quantitative. The samples of this study were 6 students of grade VIII SMP Edu Global School in Cirebon city. This study indicates that algebraic thinking ability and students' interest in learning algebra are still classified as moderate and have not reached the high category, so it needs to be improved in the learning process.

scholarly journals Stemming and Lemmatization of Tweets for Sentiment Analysis using R

2019 ◽  
Vol 8 (2) ◽  
pp. 2038-2040
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Text Analysis ◽  
Rapid Rate ◽  
Volume Data ◽  
Huge Amount ◽  
Manual Analysis ◽  
User Communities ◽  
Use Of Social Media ◽  
Day By Day

In our digital India, the use of social media like twitter, blogs and various forums is growing with the rapid rate. Thus the size of the data is becoming big day by day and in the span of this type of high varied and volume data, manual analysis would be a clumsy job. So, there is an alarming rate to analyze that large amount of data to make it suitable for analysis purpose. As a most elaborate open source platform, R has immeasurable user communities that thrives and perpetuate a huge amount of text analysis packages. So, in this paper we are analyzing movie related tweets using machine learning in R.

scholarly journals Code switching in contemporary isiZulu performance poetry

Literator ◽  
2021 ◽  
Vol 42 (1) ◽  
Author(s):  
Bongephiwe Dlamini Myeni ◽  
Nakanjani Sibiya
Keyword(s):  
Social Media ◽  
Code Switching ◽  
Oral Poetry ◽  
Current Generation ◽  
Recent Innovation ◽  
Literary Art ◽  
Performance Poetry ◽  
Recent Developments ◽  
Social Media Platforms ◽  
Constant Feature

Recent developments in isiZulu poetry have been marked by an emergence of performance poets whose poems have gained popularity with younger audiences. A constant feature in contemporary isiZulu poetry is a conscious deviation from adherence to rigid structural and formal linguistic requirements. Contemporary isiZulu poetry is also characterised by a shift from textual to performance-specific conventions that cater for radio, theatre, social-media platforms and so forth, and is more accommodative of linguistic dynamics that shape the current generation of artists and audiences. While contemporary isiZulu performance is a rather more recent innovation, it still owes its roots to oral poetry traditions and has evolved from literary art forms that were committed to memory and performed during family gatherings and communal events. This article explores code switching in contemporary isiZulu performance poetry and argues for appreciation of this phenomenon for its aesthetic appeal rather than as infringement on long-held attitudes about purity of artistic linguistic expressions. Hyme’s Ethno-poetic Theory will inform analysis of selected poems in this article. Ethno-poetic Theory focuses, amongst others, on how a performance displays literary qualities.

Hybrid Approach for Sentiment Analysis of Twitter Posts Using a Dictionary-based Approach and Fuzzy Logic Methods

2020 ◽  
Vol 16 (1) ◽  
pp. 116-145 ◽  
Author(s):  
Jamilah Rabeh Alharbi ◽  
Wadee S. Alhalabi
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Fuzzy Systems ◽  
Fuzzy Inference ◽  
Service Providers ◽  
Hybrid Approach ◽  
Cloud Service ◽  
Inference Process ◽  
Huge Amount ◽  
Fuzzy Parameters

Recently, sentiment analysis of social media has become a hot topic because of the huge amount of information that is provided in these networks. Twitter is a popular social media application offers businesses and government the opportunities to share and acquire information. This article proposes a technique that aims at measuring customers' satisfaction with cloud service providers, based on their tweets. Existing techniques focused on classifying sentimental text as either positive or negative, while the proposed technique classifies the tweets into five categories to provide better information. A hybrid approach of dictionary-based and Fuzzy Inference Process (FIP) is developed for this purpose. This direction was selected for its advantages and flexibility in addressing complex problems, using terms that reflect on human behaviors and experiences. The proposed hybrid-based technique used fuzzy systems in order to accurately identify the sentiment of the input text while addressing the challenges that are facing sentiment analysis using various fuzzy parameters.

A Survey on Opinion Mining

2017 ◽  
Vol 7 (7) ◽  
pp. 141
Author(s):  
R. Lydia Priyadharsini ◽  
M. Lovelin Ponn Felciah
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Opinion Mining ◽  
General View ◽  
Huge Amount ◽  
Customer Reviews ◽  
Personal Opinion ◽  
Clear Idea

The number of customer reviews has been increased in the recent years with the popularity of e-commerce and social media. There are many social networks in which people tend to express their personal opinion. Reviews on products help the new user to know well about the product. It helps the customers to choose the best products based on the reviews. At present, there are huge amount of opinions available in the review sites, blogs, forums etc., when the number of opinions or reviews increase to large amount, it becomes difficult to go through all the reviews and get a clear idea. Hence it is essential to summarize the opinions and provide a clear and general view for quick and better understanding. Opinion mining is the art of extracting useful opinions. This paper presents a survey on opinion mining, the techniques used and the challenges faced.

scholarly journals A Algorithm for Emotion Prediction using Twitter Dataset

2019 ◽  
Vol 8 (4) ◽  
pp. 7243-7246
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Weight Matrix ◽  
Edge Weight ◽  
Learning Approach ◽  
Huge Amount ◽  
A Algorithm ◽  
Search Terms ◽  
Machine Learning Approach ◽  
Novel Algorithm

In today's internet world almost each and everyone uses Smartphone and they are all also active in various social media. In general social media contains a huge amount of data that can be extracted and utilized to find various data insights including polarity emotion etc... This research paper mainly investigates in emotion predection using a machine learning approach . Here a novel algorithm was introduced to predict the emotion of tweets . The algorithm mainly deals with emotion Prediction by utilizing various parameters like unigram , bigram , edge weight matrix , frequency matrix and so on . Finally , the result was predicted with the emotions of the tweets . While testing with various search terms this algorithm performs well in Predicting the emotion like anger, happiness and so on .

scholarly journals Topic Detection and Tracking Techniques on Twitter: A Systematic Review

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Meysam Asgari-Chenaghlu ◽  
Mohammad-Reza Feizi-Derakhshi ◽  
Leili Farzinvash ◽  
Mohammad-Ali Balafar ◽  
Cina Motamed
Keyword(s):  
Social Media ◽  
Big Data ◽  
Topic Detection ◽  
Huge Amount ◽  
News Reporting ◽  
Topic Detection And Tracking ◽  
Detection And Tracking ◽  
Social Big Data ◽  
New Information ◽  
Text Images

Social networks are real-time platforms formed by users involving conversations and interactions. This phenomenon of the new information era results in a very huge amount of data in different forms and modalities such as text, images, videos, and voice. The data with such characteristics are also known as big data with 5-V properties and in some cases are also referred to as social big data. To find useful information from such valuable data, many researchers tried to address different aspects of it for different modalities. In the case of text, NLP researchers conducted many research studies and scientific works to extract valuable information such as topics. Many enlightening works on different platforms of social media, like Twitter, tried to address the problem of finding important topics from different aspects and utilized it to propose solutions for diverse use cases. The importance of Twitter in this scope lies in its content and the behavior of its users. For example, it is also known as first-hand news reporting social media which has been a news reporting and informing platform even for political influencers or catastrophic news reporting. In this review article, we cover more than 50 research articles in the scope of topic detection from Twitter. We also address deep learning-based methods.

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