LOOKER: a mobile, personalized recommender system in the tourism domain based on social media user-generated content

2019 ◽  
Vol 23 (2) ◽  
pp. 181-197 ◽  
Author(s):  
Sondess Missaoui ◽  
Faten Kassem ◽  
Marco Viviani ◽  
Alessandra Agostini ◽  
Rim Faiz ◽  
...  
Keyword(s):  
Social Media ◽  
Recommender System ◽  
User Generated Content ◽  
Personalized Recommender System

A Personalized Recommender System

2021 ◽  
pp. 32-42
Author(s):  
Akshit Nassa ◽  
◽  
Shubham Gupta ◽  
Pranjal Jindal ◽  
Achin Jain ◽  
...  
Keyword(s):  
Social Media ◽  
Recommender System ◽  
Consumer Preferences ◽  
Situational Factors ◽  
User Profiles ◽  
Previous Decade ◽  
Market Trends ◽  
Personalized Recommender System ◽  
Experimental Findings ◽  
The Impact

Due to social media, e-commerce, and the broader digitization of businesses, a data surge has occurred during the previous decade. The information is used to make informed decisions, forecast market trends, and identify patterns in consumer preferences. Following the widespread adoption of internet services, recommendation systems have become commonplace. The idea is to use filtering algorithms to recommend products to users who might be interested in them. Users are given recommendations for a media item such as movies by discovering user profiles of people who share similar interests. The preferences of users are first determined by allowing them to rate movies of their choosing. After some time, the recommender system will be able to better understand the user and recommend films that are more likely to get higher ratings. It also considers the impact of personal and situational factors on the user experience. In comparison to previous models, the experimental findings on the TMDB dataset provide a dependable model that is precise and generates more customized movie recommendations.

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 Accuracy improvements for cold-start recommendation problem using indirect relations in social networks

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Fu Jie Tey ◽  
Tin-Yu Wu ◽  
Chiao-Ling Lin ◽  
Jiann-Liang Chen
Keyword(s):  
Social Media ◽  
Recommender System ◽  
Mobile Networks ◽  
Reference Value ◽  
User Preferences ◽  
Digital Information ◽  
Internet Applications ◽  
Social Media Networks ◽  
Recommendation Accuracy ◽  
Gain Access

AbstractRecent advances in Internet applications have facilitated information spreading and, thanks to a wide variety of mobile devices and the burgeoning 5G networks, users easily and quickly gain access to information. Great amounts of digital information moreover have contributed to the emergence of recommender systems that help to filter information. When the rise of mobile networks has pushed forward the growth of social media networks and users get used to posting whatever they do and wherever they visit on the Web, such quick social media updates already make it difficult for users to find historical data. For this reason, this paper presents a social network-based recommender system. Our purpose is to build a user-centered recommender system to exclude the products that users are disinterested in according to user preferences and their friends' shopping experiences so as to make recommendations effective. Since there might be no corresponding reference value for new products or services, we use indirect relations between friends and “friends’ friends” as well as sentinel friends to improve the recommendation accuracy. The simulation result has proven that our proposed mechanism is efficient in enhancing recommendation accuracy.

MUBS: A Personalized Recommender System for Behavioral Activation in Mental Health

2020 ◽  
Author(s):  
Darius A. Rohani ◽  
Andrea Quemada Lopategui ◽  
Nanna Tuxen ◽  
Maria Faurholt-Jepsen ◽  
Lars V. Kessing ◽  
...  
Keyword(s):  
Mental Health ◽  
Recommender System ◽  
Behavioral Activation ◽  
Personalized Recommender System

scholarly journals Travelers’ Responsible Environmental Behavior towards Sustainable Coastal Tourism: An Empirical Investigation on Social Media User-Generated Content

2020 ◽  
Vol 13 (1) ◽  
pp. 56 ◽  
Author(s):  
Mohammad Tipu Sultan ◽  
Farzana Sharmin ◽  
Alina Badulescu ◽  
Elena Stiubea ◽  
Ke Xue
Keyword(s):  
Social Media ◽  
Structural Equation ◽  
Environmental Behavior ◽  
Relevant Literature ◽  
User Generated Content ◽  
Equation Modeling ◽  
Environmental Concerns ◽  
Destination Marketing ◽  
Coastal Tourism ◽  
Responsible Environmental Behavior

There has been increasing interest in coastal tourism, sparking a debate on the responsible environmental behavior of travelers visiting sustainable destinations. To mitigate this issue, destination marketing organizations (DMOs) and environmental activists are trying to develop strategic approaches (i.e., by using digital technologies) to enhance the sustainable behavior of travelers. Environmental responsiveness and its impact on sustainable destinations is gaining attention by companies, scholars, and institutions. However, the relevant literature has not addressed social media user-generated content regarding sustainable destinations. Sharing stakeholder knowledge, activities, and experience on social media could accomplish this goal. Hence, this paper aims to explore travelers′ responsible environmental behavior towards coastal tourism within the social media user-generated content paradigm. To measure the effect of user-generated content (UGC), i.e., cognitive triggers and affective triggers, on the responsible environmental behavior of travelers, a survey questionnaire was used to collect data (n = 506) from the world’s longest sandy sea beach, Cox’s Bazar, located in the Southern part of Bangladesh. The data were examined by structural equation modeling (SEM). The results revealed that cognitive and affective triggers of user-generated content influence travelers’ environmental concerns and attitudes, making a significant contribution to shaping responsible environmental behavior. Additionally, the findings show that environmental concerns and attitudes play a significant role in producing commitment towards a sustainable coastal tourism practice. This study contributes to the effectiveness of user-generated content for persuasive interactions with destination marketing organizations to develop sustainable tourism practices.

scholarly journals Social Media Toxicity Classification Using Deep Learning: Real-World Application UK Brexit

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1332
Author(s):  
Hong Fan ◽  
Wu Du ◽  
Abdelghani Dahou ◽  
Ahmed A. Ewees ◽  
Dalia Yousri ◽  
...  
Keyword(s):  
Social Media ◽  
Hate Speech ◽  
Modern Society ◽  
User Generated Content ◽  
Real World Application ◽  
Proposed Model ◽  
Social Media Platforms ◽  
Public Dataset ◽  
The Uk ◽  
Harmful Side Effect

Social media has become an essential facet of modern society, wherein people share their opinions on a wide variety of topics. Social media is quickly becoming indispensable for a majority of people, and many cases of social media addiction have been documented. Social media platforms such as Twitter have demonstrated over the years the value they provide, such as connecting people from all over the world with different backgrounds. However, they have also shown harmful side effects that can have serious consequences. One such harmful side effect of social media is the immense toxicity that can be found in various discussions. The word toxic has become synonymous with online hate speech, internet trolling, and sometimes outrage culture. In this study, we build an efficient model to detect and classify toxicity in social media from user-generated content using the Bidirectional Encoder Representations from Transformers (BERT). The BERT pre-trained model and three of its variants has been fine-tuned on a well-known labeled toxic comment dataset, Kaggle public dataset (Toxic Comment Classification Challenge). Moreover, we test the proposed models with two datasets collected from Twitter from two different periods to detect toxicity in user-generated content (tweets) using hashtages belonging to the UK Brexit. The results showed that the proposed model can efficiently classify and analyze toxic tweets.

Suggesting text alternatives for images in social media

2021 ◽  
pp. 1-6
Author(s):  
Letícia Seixas Pereira ◽  
João Guerreiro ◽  
André Rodrigues ◽  
André Santos ◽  
João Vicente ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Shared Responsibility ◽  
User Generated Content ◽  
Media Content ◽  
Android Application ◽  
Image Description ◽  
Visual Content ◽  
Considerable Part ◽  
The Web

Image description has been a recurrent topic on web accessibility over the years. With the increased use of social networks, this discussion is even more relevant. Social networks are responsible for a considerable part of the images available on the web. In this context, users are not only consuming visual content but also creating it. Due to this shared responsibility of providing accessible content, major platforms must go beyond accessible interfaces. Additional resources must also be available to support users in creating accessible content. Although many of today's services already support accessible media content authoring, current efforts still fail to properly integrate and guide their users through the authoring process. One of the consequences is that many users are still unaware of what an image description is, how to provide it, and why it is necessary. We present SONAAR, a project that aims to improve the accessibility of user-generated content on social networks. Our approach is to support the authoring and consumption of accessible social media content. Our prototypes currently focus on Twitter and Facebook and are available as an Android application and as a Chrome extension.

scholarly journals Detecting sentiment dynamics and clusters of Twitter users for trending topics in COVID-19 pandemic

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0253300
Author(s):  
Md Shoaib Ahmed ◽  
Tanjim Taharat Aurpa ◽  
Md Musfique Anwar
Keyword(s):  
Social Media ◽  
Public Perceptions ◽  
Intervention Strategies ◽  
User Generated Content ◽  
Time Intervals ◽  
Health Crisis ◽  
Public Health Crisis ◽  
Significant Public Health ◽  
Trending Topics ◽  
Twitter Users

COVID-19 caused a significant public health crisis worldwide and triggered some other issues such as economic crisis, job cuts, mental anxiety, etc. This pandemic plies across the world and involves many people not only through the infection but also agitation, stress, fret, fear, repugnance, and poignancy. During this time, social media involvement and interaction increase dynamically and share one’s viewpoint and aspects under those mentioned health crises. From user-generated content on social media, we can analyze the public’s thoughts and sentiments on health status, concerns, panic, and awareness related to COVID-19, which can ultimately assist in developing health intervention strategies and design effective campaigns based on public perceptions. In this work, we scrutinize the users’ sentiment in different time intervals to assist in trending topics in Twitter on the COVID-19 tweets dataset. We also find out the sentimental clusters from the sentiment categories. With the help of comprehensive sentiment dynamics, we investigate different experimental results that exhibit different multifariousness in social media engagement and communication in the pandemic period.

scholarly journals The Implementation of Knowledge Management Based On Web 2.0 on Social News Site Hipwee

2019 ◽  
Vol 4 (1) ◽  
pp. 61
Author(s):  
Mufida Cahyani
Keyword(s):  
Social Media ◽  
Knowledge Management ◽  
Web 2.0 ◽  
Network Effects ◽  
Content Management ◽  
User Participation ◽  
Online News ◽  
User Generated Content ◽  
Organizational Participation ◽  
Social Media Platforms

The emergence of various kinds of social media applications does not only affect the way people communicate, but also penetrates into the realm of online mass media. Social media platforms that carry the concept of web 2.0 namely user generated content and network effects make it easy for a news to become viral in a short time, regardless of the validity and accuracy of the news. Web 2.0 itself is a direct application of the concept of Knowledge Management (KM) which emphasizes collaboration and user participation, but in a broader domain, it is slightly different from KM which emphasizes internal organizational participation. Hipwee as one of the social media-based online news sites applies both concepts to its content management. The purpose of this study was to analyze the extent of the application of KM in relation to Web 2.0. The method used to explore data through interviews with Hipwee managers and direct observation to the office location and also the Hipwee site. The results obtained are that the adaptation of the KM concept has not been applied to Web 2.0 on the Hipwee site, namely the concept of data mining, while the Web 2.0 concept has been applied to KM, namely unbounded collaboration, user generated content and network effects.

Sign in / Sign up

Export Citation Format

Share Document