Breaking Physical Barriers With Mobile Technologies

Considering the growing popularity of mobile technologies and therefore social media tools, the idea of this study is not to promote or romanticise a social media tool but to explore the potential of social media for educational use by presenting a specific example. The study also aims to bring a deeper understanding of how mobile applications could be used to foster language education and consider their possible potential in education. Unlike the common trend investigating English vocabulary in the field, this study does not expose students to word lists but attempts to support the curriculum that students have to follow in their formal education. In this context, this chapter suggests an example of going beyond the physical constraint of language classroom by providing learners informal opportunities to practise English outside school in various contexts by using one of the most popular tools, namely WhatsApp.

Topic Modeling and Sentiment Analysis of Electric Vehicles of Twitter Data

Twitter is a well-known social media tool for people to communicate their thoughts and feelings about products or services. In this project, I collect electric vehicles related user tweets from Twitter using Twitter API and analyze public perceptions and feelings regarding electric vehicles. After collecting the data, To begin with, as the first step, I built a pre-processed data model based on natural language processing (NLP) methods to select tweets. In the second step, I use topic modeling, word cloud, and EDA to examine several aspects of electric vehicles. By using Latent Dirichlet allocation, do Topic modeling to infer the various topics of electric vehicles. The topic modeling in this study was compared with LSA and LDA, and I found that LDA provides a better insight into topics, as well as better accuracy than LSA.In the third step, the “Valence Aware Dictionary (VADER)” and “sEntiment Reasoner (SONAR)” are used to analyze sentiment of electric vehicles, and its related tweets are either positive, negative, or neutral. In this project, I collected 45000 tweets from Twitter API, related hashtags, user location, and different topics of electric vehicles. Tesla is the top hashtag Twitter users tweeted while sharing tweets related to electric vehicles. Ekero Sweden is the most common location of users related to electric vehicles tweets. Tesla is the most common word in the tweets related to electric vehicles. Elon-musk is the common bi-gram found in the tweets related to electric vehicles. 47.1% of tweets are positive, 42.4% are neutral, and 10.5% are negative as per VADER Finally, I deploy this project work as a fully functional web app.

Cone beam computed tomography in the diagnosis of Stafne bone cavity: Report of seven cases and review of the open-access literature.

Stafne bone cavity (SBC) is a rare entity to find on panoramic radiography and on cone beam computed tomography. We reviewed in a systematic way the open-access literature from PubMed and DOAJ. We also proposed a new methodology consisting of collaboration with private practitioners, application of participative science approach, and open science practices, and using social media tool to obtain and describe seven different cases of SBC. We finally propose a new matrix table for classification of anatomical types of SBC already described and those yet to be described in open-access literature.

COMMUNICATION EFFECTIVENESS OF SURABAYA CITY GOVERNMENT THROUGH TWITTER AND FACEBOOK

Advances in information and communication technology encourage the government as a stakeholder to have social media accounts. Likewise, the community is also required to have social media as a means of communication. The importance of social media has a very significant impact, especially in the field of government, for example as a medium in conveying suggestions and complaints from the public to the government or vice versa. Twitter and Facebook are some of the social media that are very popular with Indonesians. Including the Surabaya City Government, to support and develop policy programs made, they use this social media tool as an effective medium of communication. The purpose of this study was to determine the level of effectiveness of Surabaya city government communication via Twitter and Facebook. The research method used is descriptive qualitative by utilizing the Nvivo application to process the data. In this study, there are several assessment indicators used as benchmarks, namely (1) Accuracy, (2) Creativity, (3) Activeness, (4) Interaction, (5) Transparency. From the research results, it is known that the effectiveness of communication via Twitter is better than Facebook in terms of accurate information, creativity, activeness, and transparency. Meanwhile, in terms of interaction, Facebook is higher. Therefore, the Government is required to be even more innovative in conveying information to the public, so that people have an interest in knowing information about government and policies that have been announced.

Virtual Face to Face Meeting for Non-Technical Personnel

Covid-19 has impacted profoundly the business environment. Information and Communication Technology (ICT) becomes not only the major platform but also sustains the existence and running most business. Retail business becomes more dependent on technology. Small Business Enterprises (SME) have to jump and become savvy in ICT. The SME supply chain and marketing environment are moving toward ICT based platforms. On the other side the penetration of social media tool especially smartphone is widely spread. It can be safely assumed that every job holder whether entrepreneur, employee, or professionals or craftspeople is familiar with smartphones. The gap that must be bridged is using smartphone for business purposes. One of the business requirements that are not easy to replace is face to face communications. As Internet is ubiquitous and smartphones can easily access the Internet, there are numerous application that can resides both in computers and smartphones. The application that is closely similar to face to face meeting is known as Video Conference call. With this application it is possible to perform business briefing any time and anywhere provided there is Internet access. As business communication is not limited to technically savvy parties, a supportive system must be selected and introduced to them. We select Zoom as the application and develop a simple training syllabus. The syllabus has been implemented to a retail chain.

YOUTUBE DATA ANALYSIS USING HADOOP FRAMEWORK

— Analysis of consistent and structured data has seen huge success in past decades. Where the analysis of unstructured data in the form of multimedia format remains a challenging task. YouTube is one of the most used and popular social media tool. The main aim of this paper is to analyze the data that is generated from YouTube that can be mined and utilized. API (Application Programming Interface) and going to be stored in Hadoop Distributed File System (HDFS). Dataset can be analyzed using MapReduce. Which is used to identify the video categories in which most number of videos are uploaded. The objective of this paper is to demonstrate Hadoop framework, to process and handle big data there are many components. In the existing method, big data can be analyzed and processed in multiple stages by using MapReduce. Due to huge space consumption of each job, Implementing iterative map reduce jobs is expensive. A Hive method is used to analyze the big data to overcome the drawbacks of existing methods, which is the state-ofthe-art method. The hive works by extracting the YouTube information by generating API (Application Programming Interface) key and uses the SQL queries.

The Gray Legion: Information Warfare Within Our Gates

The information environment, once viewed as an unassailed common for human knowledge, has revealed itself to be a vector for malicious narratives in the ongoing battle for global hegemony. Since 2014, the United States has been under siege from information attacks on multiple fronts, from cyber infrastructure and goods to the cognitive outlooks of its citizenry. Disinformation as a social media tool represents a novel and grave danger to democracy; it serves as a means for sowing unrest and influencing policy changes while enabling conventional conflict or—in the best case for those who would exploit and manipulate narratives—avoiding it entirely. In this article, we identify the harbinger of a dire threat that circles outside, and now inside, the United States' walls by exploring the theoretical dynamics of foreign, state-sponsored disinformation in democracies throughout the West. We examine the mechanisms through which this approach operates and why it is Russia’s preferred course of action.

Beyond the hashtag: describing and understanding the full impact of the #BJSConnect tweet chat May 2019

Background Twitter engagement between surgeons provides opportunities for international discussion of research and clinical practice. Understanding how surgical tweet chats work is important at a time when increasing reliance is being placed on virtual engagement because of the COVID-19 pandemic. Methods Individual tweets from the May 2019 #BJSConnect tweet chat were extracted using NodeXL, complemented by Twitter searches in an internet browser to identify responses that had not used the hashtag. Aggregate estimates of tweet views were obtained from a third-party social media tool (Twitonomy) and compared with official Twitter Analytics measurements. Results In total 37 Twitter accounts posted 248 tweets or replies relating to the tweet chat. A further 110 accounts disseminated the tweets via retweeting. Only 58.5 per cent of these tweets and 35 per cent of the tweeters were identified through a search for the #BJSConnect hashtag. The rest were identified by searching for replies (61), quoting tweets (20), and posts by @BJSurgery that used the hashtag but did not appear in the Twitter search (22). Studying all tweets revealed complex branching discussions that went beyond the discussed paper’s findings. Third-party estimates of potential reach of the tweet chat were greatly exaggerated. Conclusion Understanding the extent of the discussion generated by the #BJSConnect tweet chat required looking beyond the hashtag to identify replies and other responses, which was time-consuming. Estimates of reach using a third-party tool were unreliable.

Mining and YouTube Data Analysis using Hadoop

Analysis of structured and consistent data has seen remarkable success in past decades. Whereas, the analysis of unstructured data in the form of multimedia format remains a challenging task. YouTube is one of the most popular and used social media tool. It reveals the community feedback through comments for published videos, number of likes, dislikes, number of subscribers for a particular channel. The main objective of this work is to demonstrate by using Hadoop concepts, how data generated from YouTube can be mined and utilized to make targeted, real time and informed decisions. In our paper, we analyze the data to identify the top categories in which the most number of videos are uploaded. This YouTube data is publicly available and the YouTube data set is described below under the heading Data Set Description. The dataset will be fetched from the Google using the YouTube API (Application Programming Interface) and going to be stored in Hadoop Distributed File System (HDFS). Using MapReduce we are going to analyze the dataset to identify the video categories in which most number of videos are uploaded. The objective of this paper is to demonstrate Apache Hadoop framework concepts and how to make targeted, real-time and informed decisions using data gathered from YouTube.

Society and people diagnosed with autism spectrum disorder: an analysis of message descriptors of social media

The authors investigate the process of humanization of society in relation to people with autism spectrum disorders and its relationship with the reception of problems of this category of population by society. The authors based on the descriptors of messages in social media published in the digital media space. The article reveals the relationship between the content of messages in social media, as well as the tools of this type of media and the overall degree of humanization of society at both social and political levels. The typological features of such a social media tool as a hashtag, when covering the problems of people with autism spectrum disorders, as well as the impact of these features on the reception of messages on this topic by both domestic and English-speaking users are noted.