scholarly journals A social media-based framework for tourist behaviour analysis and characterization in urban environments

2021 ◽  
Vol 4 ◽  
pp. 1-8
Author(s):  
Francisco Porras-Bernardez ◽  
Georg Gartner
Keyword(s):  
Social Media ◽  
Language Processing ◽  
Spatial Clustering ◽  
Distribution Patterns ◽  
Urban Environments ◽  
Alternative Analysis ◽  
Good Potential ◽  
Media Platform ◽  
Behaviour Study ◽  
Tourist Behaviour

Abstract. Tourism is a very important and fast growing industry worldwide that has generated 25% of all global net new jobs during the last 5 years. New tools can be valuable for relaunching the sector and provide alternative analysis and segmentation capabilities to organizations involved. We present an analysis and visualization framework for tourist behaviour study and segmentation based on tested methods and technologies, combined and extended in an innovative way. Our framework uses Flickr data as input and classifies users according to country of origin. Then, urban distribution patterns are obtained in two different spatial levels by using [Network] Kernel Density Estimation in 1D and 2D spaces, as well as spatial clustering with HDBSCAN. Basic Natural Language Processing is applied to extract and visualize semantics generated in the social media platform and a visualization of typologies of Points of Interest by nationality is proposed for the development of tourism dashboards. We have applied our framework to three European cities of different size to test the segmentation capabilities of the approach. Results suggest a good potential for tourism management in urban environments.

scholarly journals MO’ CHARACTERS MO’ PROBLEMS: ONLINE SOCIAL MEDIA PLATFORM CONSTRAINTS AND MODES OF COMMUNICATION

2020 ◽  
Author(s):  
Lewis Mitchell ◽  
Joshua Dent ◽  
Joshua Ross
Keyword(s):  
Social Media ◽  
Language Processing ◽  
Large Scale ◽  
English Language ◽  
Length Change ◽  
Reading Level ◽  
Online Social Media ◽  
Social Media Platforms ◽  
Media Platform ◽  
Processing Techniques

It is widely accepted that different online social media platforms produce different modes of communication, however the ways in which these modalities are shaped by the constraints of a particular platform remain difficult to quantify. On 7 November 2017 Twitter doubled the character limit for users to 280 characters, presenting a unique opportunity to study the response of this population to an exogenous change to the communication medium. Here we analyse a large dataset comprising 387 million English-language tweets (10% of all public tweets) collected over the September 2017--January 2018 period to quantify and explain large-scale changes in individual behaviour and communication patterns precipitated by the character-length change. Using statistical and natural language processing techniques we find that linguistic complexity increased after the change, with individuals writing at a significantly higher reading level. However, we find that some textual properties such as statistical language distribution remain invariant across the change, and are no different to writings in different online media. By fitting a generative mathematical model to the data we find a surprisingly slow response of the Twitter population to this exogenous change, with a substantial number of users taking a number of weeks to adjust to the new medium. In the talk we describe the model and Bayesian parameter estimation techniques used to make these inferences. Furthermore, we argue for mathematical models as an alternative exploratory methodology for "Big" social media datasets, empowering the researcher to make inferences about the human behavioural processes which underlie large-scale patterns and trends.

scholarly journals Twitter Spam Detection using Pre-trained Model

2019 ◽  
Vol 8 (4) ◽  
pp. 10620-10623
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Language Processing ◽  
Spam Detection ◽  
Social Media Platform ◽  
Machine Learning Model ◽  
The Social ◽  
Media Platform ◽  
E Mail ◽  
Day By Day

In the age of technology social media platform is becoming a great companion for expressing the thoughts, information, and opinion. It became the powerful tool for every person who wants to expand their networks of people beyond the physical boundation. We are living at that age where various categories of social media platform available according to work needed, it may be Facebook, LinkedIn, WhatsApp or Twitter. We are focusing our work on Twitter, It is also known as microblogging site which provides service to express the opinion in limited words. As the popularity of twitter is growing day by day users are joining the platform very fast, as it happens another side many spammers are also taking undue advantages of this platform, for any social media platform it is very important to maintain the secure, safer and trustworthy environment for their legitimate users. Twitter spams are more harmful than e-mail spam because of their higher clickthrough rate, as in the social network if someone trusted some spam a genuine post than it is higher chance that the persons in the network might also trust on that spam post and may click on it. There are plenty of methods available to handle the task of twitter spam detection problem, we are solving this problem of twitter spam at tweet level.Pre-trained models are some breakthrough in the journey of machine learning and natural language processing after their advancement they are of great help. Here we are using Bidirectional Encoder Representation from Transformer (BERT) model to solve the problem as our task is to solve the problem of imbalance dataset as well as the multilingual dataset, BERT makes a clear distinction in this type of task, the main advantage of this type’s model is that we don’t have to collect millions of data for better performance of the machine learning model.

scholarly journals Lexicon based Chinese language sentiment analysis method

2019 ◽  
Vol 16 (2) ◽  
pp. 639-655
Author(s):  
Jinyan Chen ◽  
Susanne Becken ◽  
Bela Stantic
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Chinese Language ◽  
Big Data Analytics ◽  
Limited Attention ◽  
Analysis Method ◽  
Media Platform ◽  
Chinese Social Media

The growing number of social media users and vast volume of posts could provide valuable information about the sentiment toward different locations, services as well as people. Recent advances in Big Data analytics and natural language processing often means to automatically calculate sentiment in these posts. Sentiment analysis is challenging and computationally demanding task due to the volume of data, misspelling, emoticons as well as abbreviations. While significant work was directed toward the sentiment analysis of English text there is limited attention in literature toward the sentiment analytic of Chinese language. In this work we propose method to identify the sentiment in Chinese social media posts and to test our method we rely on posts sent by visitors of Great Barrier Reef by users of most popular Chinese social media platform Sina Weibo. We elaborate process of capturing of weibo posts, describe a creation of lexicon as well as develop and explain algorithm for sentiment calculation. In case study, related to sentiment toward the different GBR destinations, we demonstrate that the proposed method is effective in obtaining the information and is suitable to monitor visitors? opinion.

Sosyal medyada Suriye’li sığınmacılara yönelik algı: bir sözlük değerlendirmesi

2017 ◽  
Vol 4 (2) ◽  
pp. 185-200 ◽  
Author(s):  
Servet Kardeş ◽  
Çağla Banko ◽  
Berrin Akman
Keyword(s):  
Qualitative Research ◽  
Social Media ◽  
Content Analysis ◽  
Syrian Refugees ◽  
Analysis Method ◽  
Social Media Platform ◽  
Content Analysis Method ◽  
Negative News ◽  
Media Platform ◽  
Made In

Bu araştırmada sığınmacılara yönelik paylaşımların yapıldığı sosyal medyada yer alan sözlüklerden birinde sığınmacılara yönelik algıya bakılmıştır. Yöntem olarak nitel desende olan bu çalışmada, bir sosyal medya sitesinde yer alan paylaşımlar içerik analizi yoluyla derinlemesine incelenip yorumlanmıştır. Araştırmanın sonucunda sosyal medya kullanıcılarının sığınmacıları büyük bir güvensizlik ortamı ve huzursuzluk yaratan bireyler olarak gördükleri saptanmış, sığınmacılarla yaşanan deneyimlerin ve medyadaki haberlerin bu düşüncelerin oluşmasında etkisinin olduğu belirlenmiştir. Bunun yanında sosyal medya kullanıcılarının devletin sığınmacılar konusunda yanlış politika izlediğini düşündükleri ve sığınmacılar için etkili bir planlama yapılmadığını ifade ettikleri görülmüştür. Çalışmanın sonuçları doğrultusunda medyada sığınmacılar hakkında çıkan haberlerde olumsuz ve şiddet temalı haberlerin azaltılması, Suriyeli sığınmacıların durumu, sahip oldukları haklar ve topluma yansımaları hakkında doğru ve bilgilendirici kamu spotları hazırlanması ayrıca sığınmacıların topluma entegre olma sürecinin her basamağında daha planlı ve etkili bir yol izlenmesi önerilebilir.ABSTRACT IN ENGLISHPerceptions about Syrian refugees on social media: an evaluation of a social media platformIn this research, posts which are about Syrian refugees were published in a social media platform, called as “sözlük” were investigated. The research is a qualitative research. The posts in this platform are analyzed with content analysis method. According to results of analyses, social media users see Syrian refugees as people who create an insecure and a restless environment. The experiences people had with them and news have an effect on this view. In addition, social media users think that government made inappropriate policies and ineffective plans about Syrian refugees. It is suggested negative news about Syrian refugees should be decreased and government should make safer policies. In addition, adaptation of refugees to society should be made in more planned and effective way.

Value cocreation behavior of customers and companies on the Weibo social media platform

2020 ◽  
Vol 48 (3) ◽  
pp. 1-11
Author(s):  
Huiqin Zhang ◽  
Hai Lan ◽  
Xudong Chen
Keyword(s):  
Social Media ◽  
Service Quality ◽  
Customer Value ◽  
Two Dimensions ◽  
Customer Participation ◽  
Citizenship Behavior ◽  
Generation Process ◽  
Social Media Platform ◽  
Value Cocreation ◽  
Media Platform

The Weibo social media platform in China has an important role in the value-generation process between a company and a customer. We investigated the relationship between the service quality provided on a company's Weibo page and the two dimensions of customer value cocreation behavior, namely, participation and citizenship, as well as the moderating effect of collectivism on this relationship. Participants were 354 active users of Weibo. Our findings confirmed that the service quality provided on a company's Weibo page was critical to the generation of customer value cocreation behavior. Further, collectivism moderated this relationship, with higher levels of collectivism strengthening the Weibo page service quality and customer value cocreation behavior relationship. In addition, customer citizenship behavior was positively related to customer perceptions of brand image, whereas customer participation was not. Implications for companies in the Chinese context are discussed.

Wykorzystanie mediów społecznościowych w komunikacji z klientem na przykładzie firm sektora piwowarskiego

2015 ◽  
pp. 161-176 ◽  
Author(s):  
Piotr Szamrowski ◽  
Adam Pawlewicz
Keyword(s):  
Social Media ◽  
Public Relations ◽  
Small Enterprises ◽  
Brewing Industry ◽  
Video Sharing ◽  
Advantages And Disadvantages ◽  
Media Platform ◽  
The Individual ◽  
Media Channels ◽  
Regional Character

The main objective of this paper is to identify the platforms and social media tools utilized by the brewing industry in communication with the stakeholders, mainly with potential clients. In addition, the study sought to determine the nature of the published content, identify those responsible for their management, and present the advantages and disadvantages of their conduct in communication and creating the image of the company. The results indicate that only 25% of the surveyed companies do not use social media in PR. This applies only to small enterprises, with regional character. All the major brewing companies in their public relations activities use at least one type of social media, focusing in most cases on social networking (Facebook) and Video Sharing (YouTube). In addition, some of the largest brands included in the individual equity groups have their own social media channels used to communicate with the stakeholders. General promotion of company products and, what is very important, creating a dialogue with social media platform community, were seen as the most important benefits of using social media.

Earth-Science Outreach Using an Integrated Social Media Platform

GSA Today ◽  
2017 ◽  
Author(s):  
C.J. Spencer ◽  
K.L. Gunderson ◽  
C.W. Hoiland ◽  
W.K. Schleiffarth
Keyword(s):  
Social Media ◽  
Earth Science ◽  
Science Outreach ◽  
Social Media Platform ◽  
Media Platform
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