scholarly journals Social Media Analytics for Sentiment Analysis and Event Detection in Smart Cities

2018 ◽  
Author(s):  
Aysha Al Nuaimi ◽  
Aysha Al Shamsi ◽  
Amna Al Shamsi ◽  
Elarbi Badidi
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Event Detection ◽  
Smart Cities ◽  
Social Media Analytics

scholarly journals The Power of Social Media Analytics: Text Analytics Based on Sentiment Analysis and Word Clouds on R

2018 ◽  
Vol 22 (1/2018) ◽  
pp. 25-38
Author(s):  
Ahmed Imran KABIR ◽  
Ridoan KARIM ◽  
Shah NEWAZ ◽  
Muhammad Istiaque HOSSAIN
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Social Media Analytics ◽  
Text Analytics ◽  
Word Clouds

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.

scholarly journals Social Media Analytics of the Internet of Things

2021 ◽  
Author(s):  
Jim Scheibmeir ◽  
Yashwant K. Malaiya
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Internet Of Things ◽  
Smart Cities ◽  
The Internet ◽  
Social Media Analytics ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
Internet Of Things Technology ◽  
The Internet Of Things

Abstract The Internet of Things technology offers convenience and innovation in areas such as smart homes and smart cities. Internet of Things solutions require careful management of devices and the risk mitigation of potential vulnerabilities within cyber-physical systems. The Internet of Things concept, its implementations, and applications are frequently discussed on social media platforms. This article illuminates the public view of the Internet of Things through a content-based analysis of contemporary conversations occurring on the Twitter platform. Tweets can be analyzed with machine learning methods to converge the volume and variety of conversations into predictive and descriptive models. We have reviewed 684,503 tweets collected in a two-week period. Using supervised and unsupervised machine learning methods, we have identified interconnecting relationships between trending themes and the most mentioned industries. We have identified characteristics of language sentiment which can help to predict popularity within the realm of IoT conversation. We found the healthcare industry as the leading use case industry for IoT implementations. This is not surprising as the current Covid-19 pandemic is driving significant social media discussions. There was an alarming dearth of conversations towards cybersecurity. Only 12% of the tweets relating to the Internet of Things contained any mention of topics such as encryption, vulnerabilities, or risk, among other cybersecurity-related terms.

scholarly journals Sentiment Analysis of Social Survey Data for Local City Councils

2022 ◽  
Vol 11 (1) ◽  
pp. 7
Author(s):  
Marianna Lepelaar ◽  
Adam Wahby ◽  
Martha Rossouw ◽  
Linda Nikitin ◽  
Kanewa Tibble ◽  
...  
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Survey Data ◽  
Smart Cities ◽  
Social Indicators ◽  
Media Analysis ◽  
Social Surveys ◽  
Analysis Techniques ◽  
The Social ◽  
The City

Big data analytics can be used by smart cities to improve their citizens’ liveability, health, and wellbeing. Social surveys and also social media can be employed to engage with their communities, and these can require sophisticated analysis techniques. This research was focused on carrying out a sentiment analysis from social surveys. Data analysis techniques using RStudio and Python were applied to several open-source datasets, which included the 2018 Social Indicators Survey dataset published by the City of Melbourne (CoM) and the Casey Next short survey 2016 dataset published by the City of Casey (CoC). The qualitative nature of the CoC dataset responses could produce rich insights using sentiment analysis, unlike the quantitative CoM dataset. RStudio analysis created word cloud visualizations and bar charts for sentiment values. These were then used to inform social media analysis via the Twitter application programming interface. The R codes were all integrated within a Shiny application to create a set of user-friendly interactive web apps that generate sentiment analysis both from the historic survey data and more immediately from the Twitter feeds. The web apps were embedded within a website that provides a customisable solution to estimate sentiment for key issues. Global sentiment was also compared between the social media approach and the 2016 survey dataset analysis and showed some correlation, although there are caveats on the use of social media for sentiment analysis. Further refinement of the methodology is required to improve the social media app and to calibrate it against analysis of recent survey data.

Sentiment Analysis of Game Review Using Machine Learning in a Hadoop Ecosystem

2020 ◽  
pp. 145-165
Author(s):  
Arvind Panwar ◽  
Vishal Bhatnagar
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Sentiment Analysis ◽  
Experimental Work ◽  
Electronic Device ◽  
Social Media Analytics ◽  
Social Game ◽  
Hadoop Ecosystem ◽  
Global Platform ◽  
The Web

Internet, & more unambiguously the creation of WWW in the early 1990s, helped people to build an interconnected global platform where information can be stored, shared, and consumed by anyone with an electronic device which has the ability to connect to the Web. This provides a way of putting together lots of information, ideas, and opinion. An interactive platform was born to post content, messages, and opinions under one roof, and the platform is known as social media. Social media has acquired massive popularity and importance that why today almost everyone can't stay away from it. Social media is not only a medium for people to express their thoughts, moreover, but it is also a very powerful tool which can be used by businesses to focus on new and existing customers and increase profit with the help of social media analytics. This paper starts with a discussion on social media with its significance & pitfalls. Later on, this paper presents a brief introduction of sentiment analysis in social media and give an experimental work on sentiment analysis in a social game review.

scholarly journals Development of Social Media Analytics System for Emergency Event Detection and Crisis Management

2021 ◽  
Vol 68 (3) ◽  
pp. 3079-3100
Author(s):  
Shaheen Khatoon ◽  
Majed A. Alshamari ◽  
Amna Asif ◽  
Md Maruf Hasan ◽  
Sherif Abdou ◽  
...  
Keyword(s):  
Social Media ◽  
Crisis Management ◽  
Event Detection ◽  
Social Media Analytics ◽  
Emergency Event
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