scholarly journals Tourist Sentiment Mining Based on Deep Learning

2021 ◽  
Author(s):  
Weijun Li ◽  
Qun Yang ◽  
Wencai Du
Keyword(s):  
Deep Learning ◽  
User Generated Content ◽  
The Internet ◽  
Emotion Detection ◽  
Accurate Identification ◽  
Sentiment Mining ◽  
Sentiment Orientation ◽  
Online Travel ◽  
Enormous Number

Mining the sentiment of the user on the internet via the context plays a significant role in uncovering the human emotion and in determining the exactness of the underlying emotion in the context. An increasingly enormous number of user-generated content (UGC) in social media and online travel platforms lead to development of data-driven sentiment analysis (SA), and most extant SA in the domain of tourism is conducted using document-based SA (DBSA). However, DBSA cannot be used to examine what specific aspects need to be improved or disclose the unknown dimensions that affect the overall sentiment like aspect-based SA (ABSA). ABSA requires accurate identification of the aspects and sentiment orientation in the UGC. In this book chapter, we illustrate the contribution of data mining based on deep learning in sentiment and emotion detection.

Chinese Social Media Platforms and Microblogging in the Context of Public Diplomacy

Communicology ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 167-179
Author(s):  
E.S. Nadezhkina
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Public Diplomacy ◽  
User Generated Content ◽  
The Internet ◽  
Interactive Communication ◽  
Network Interaction ◽  
Social Media Platforms ◽  
The Right ◽  
Chinese Social Media

The term “digital public diplomacy” that appeared in the 21st century owes much to the emergence and development of the concept of Web 2.0 (interactive communication on the Internet). The principle of network interaction, in which the system becomes better with an increase in the number of users and the creation of user-generated content, made it possible to create social media platforms where news and entertainment content is created and moderated by the user. Such platforms have become an expression of the opinions of various groups of people in many countries of the world, including China. The Chinese segment of the Internet is “closed”, and many popular Western services are blocked in it. Studying the structure of Chinese social media platforms and microblogging, as well as analyzing targeted content is necessary to understand China’s public opinion, choose the right message channels and receive feedback for promoting the country’s public diplomacy. This paper reveals the main Chinese social media platforms and microblogging and provides the assessment of their popularity, as well as possibility of analyzing China’s public opinion based on “listening” to social media platforms and microblogging.

scholarly journals Securing IoT Devices: A Robust and Efficient Deep Learning with a Mixed Batch Adversarial Generation Process for CAPTCHA Security Verification

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1798
Author(s):  
Stephen Dankwa ◽  
Lu Yang
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Process Model ◽  
Good Practice ◽  
Knowledge Exchange ◽  
Turing Test ◽  
The Internet ◽  
Generation Process ◽  
Adversarial Attack ◽  
Mixed Batch

The Internet of Things environment (e.g., smart phones, smart televisions, and smart watches) ensures that the end user experience is easy, by connecting lives on web services via the internet. Integrating Internet of Things devices poses ethical risks related to data security, privacy, reliability and management, data mining, and knowledge exchange. An adversarial machine learning attack is a good practice to adopt, to strengthen the security of text-based CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart), to withstand against malicious attacks from computer hackers, to protect Internet of Things devices and the end user’s privacy. The goal of this current study is to perform security vulnerability verification on adversarial text-based CAPTCHA, based on attacker–defender scenarios. Therefore, this study proposed computation-efficient deep learning with a mixed batch adversarial generation process model, which attempted to break the transferability attack, and mitigate the problem of catastrophic forgetting in the context of adversarial attack defense. After performing K-fold cross-validation, experimental results showed that the proposed defense model achieved mean accuracies in the range of 82–84% among three gradient-based adversarial attack datasets.

Spoken content retrieval and understanding using deep learning

Impact ◽  
2021 ◽  
Vol 2021 (1) ◽  
pp. 9-11
Author(s):  
Lin-shan Lee
Keyword(s):  
Deep Learning ◽  
Scientific Community ◽  
Online Courses ◽  
The Internet ◽  
Human Voice ◽  
Content Retrieval ◽  
Youtube Videos ◽  
Access Information ◽  
Teaching Machines

Spoken content refers to all content over the Internet which includes human voice, essentially those in multimedia, such As YouTube videos and online courses. Today such content is retrieved via Google primarily based on human-generated text labels, because Google can only retrieve text over the Internet. The goal of this project is to produce technologies to retrieve accurately and efficiently such spoken content directly based on the included audio sounds instead of text labels, because machines today can listen to human voice just as they can read the text. The long term goal is to create a spoken version of Google, which may revolutionize the ways in which humans access information and improve their knowledge. Professor Lin-shan Lee at National Taiwan University is leading this project. He has been a distinguished leader in the global scientific community for the area of teaching machines to speak and listen to human voice for many years.

scholarly journals Research on the Design of Government Affairs Platform in the Context of Big Data

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Qian Huang ◽  
Xue Wen Li
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Learning Algorithm ◽  
The Internet ◽  
Chinese Government ◽  
Development Status ◽  
Deep Learning Algorithm ◽  
Government Management ◽  
The Government ◽  
The Impact

Big data is a massive and diverse form of unstructured data, which needs proper analysis and management. It is another great technological revolution after the Internet, the Internet of Things, and cloud computing. This paper firstly studies the related concepts and basic theories as the origin of research. Secondly, it analyzes in depth the problems and challenges faced by Chinese government management under the impact of big data. Again, we explore the opportunities that big data brings to government management in terms of management efficiency, administrative capacity, and public services and believe that governments should seize opportunities to make changes. Brainlike computing attempts to simulate the structure and information processing process of biological neural network. This paper firstly analyzes the development status of e-government at home and abroad, studies the service-oriented architecture (SOA) and web services technology, deeply studies the e-government and SOA theory, and discusses this based on the development status of e-government in a certain region. Then, the deep learning algorithm is used to construct the monitoring platform to monitor the government behavior in real time, and the deep learning algorithm is used to conduct in-depth mining to analyze the government's intention behavior.

scholarly journals Motivation for ‘Consumer–Producer‘ Interactions in Tourism: Disintermediation and Scope for Travel Agencies

2016 ◽  
Vol 11 (1) ◽  
pp. 31-45
Author(s):  
Fernandes Anthony Jovial ◽  
Alex Emy
Keyword(s):  
The Internet ◽  
Buying Behavior ◽  
Structured Interviews ◽  
Online Transactions ◽  
Travel Agents ◽  
Changing Trends ◽  
Travel Agencies ◽  
Online Travel

Increase in accessibility to the internet and consumer’s faith in conducting online transactions, have paved way for a steady change in how consumers plan and buy their holidays. The role of traditional travel agents and online travel portals, as sources most knowledgeable about holiday destinations is on the wane due to the emergence of online reviewing platforms, and easily accessible and first-hand information from the service producers. Consumers today prefer to approach service producers such as resorts, restaurants, transport providers and guides to book their services. Given this scenario, this paper attempts to determine the catalyst for the changing trends in tourist buying behavior, the role of the internet and whether travel agents are aware of the said changes. The paper also looks at possible opportunities for travel agents to expand their products’ portfolio to maintain or increase their revenue in tandem with the changes in the industry. The study takes into consideration responses received from 75 tourists and structured interviews conducted with sixteen travel agents.

scholarly journals THE STEAM PLATFORM ECONOMY: CAPITALISING FROM PLAYER-DRIVEN ECONOMIES ON THE INTERNET.

2020 ◽  
Author(s):  
Anne Mette Thorhauge
Keyword(s):  
Third Party ◽  
User Generated Content ◽  
The Internet ◽  
Economic Perspective ◽  
Economic Action ◽  
Potential Source ◽  
Attention Economy ◽  
Platform Economy ◽  
Game Platform

With this paper I aim to analyse and discuss the Steam game platform in a platform economic perspective. I will argue that Steam represents a special type of platform economy due to its roots in gaming economies: Steam’s platform economy can be seen as a specific way of capitalising on the player-driven economies that arise within and beyond key game titles offered on the platform. The API offered to third party developers on Steams websites can be described as a ‘palette of monetization strategies’ that run from simple retail models in the game store, over various ways of integrating user generated content in the Steam Workshop to the prospects of harnessing and capitalising from players’ economic action in the Community market. A look some of the most-played games titles shows that this gives rise to a variety of diverse monetization strategies. Many of those monetization strategies move beyond advertising and the attention economy, making players trades another potential source of income. In all cases, of course, Steam gets its share.

scholarly journals When Copyright is Wrong

2021 ◽  
Author(s):  
William Urquhart
Keyword(s):  
Detection System ◽  
Copyright Infringement ◽  
Modern Technology ◽  
User Generated Content ◽  
The Internet ◽  
Fair Dealing ◽  
Media Companies ◽  
Detection Systems ◽  
Research Findings ◽  
Controversial Area

While copyright legally protects the ownership of created works, fair dealing with copyrighted content has become a problematic topic with the rise of user-generated content. User-generated content can be easily produced with modern technology and shared on the internet. This has resulted in websites having complicated processes for dealing with copyrighted content and many have introduced automated copyright detection systems to limit their liabilities of copyright infringement. Since automated copyright detection systems have been introduced, they have fundamentally changed the way copyright infringement is managed online. However, a problem arises with automated copyright detection systems as they are incapable of detecting fair dealing. Fair dealing is a provision under New Zealand’s Copyright Act 1994 that allows the use of copyrighted content in certain cases. Consequently, this has turned into a controversial area between content creators and copyright holders as most user-generated content usually contains copyrighted content. Copyright laws also favour mass media companies as they control significant copyright properties, and this plays a key role in the economy. For this reason, copyright genuinely tends to focus on the rights of copyright holders and not so much for users of copyrighted content. Furthermore, New Zealand's Copyright Act 1994 has not been updated since 2011 and has become unsuitable for modern forms of creation on the internet. This research portfolio investigates the problematic issues concerning New Zealand’s Copyright Act 1994 with its application to user-generated content and YouTube’s automated copyright detection system called ‘Content ID’. To express research findings, this research portfolio contains a user-generated documentary and several other proposed methods of bypassing Content ID.

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