scholarly journals Predictive Analytical Model for Microblogging Data Using Asset Bubble Modelling

2020 ◽  
Vol 14 (2) ◽  
pp. 108-118
Author(s):  
Srinidhi Hiriyannaiah ◽  
Siddesh G.M. ◽  
Srinivasa K.G.
Keyword(s):  
Social Media ◽  
Information Diffusion ◽  
Predictive Analytics ◽  
Heterogeneous Systems ◽  
Asset Bubble ◽  
Proposed Model ◽  
Different Types ◽  
Social Media Platforms ◽  
Types Of Information ◽  
Better Than

In recent days, social media plays a significant role in the ecosystem of the big data world and its different types of information. There is an emerging need for collection, monitoring, analyzing, and visualizing the different information from various social media platforms in different domains like businesses, public administration, and others. Social media acts as the representative with numerous microblogs for analytics. Predictive analytics of such microblogs provides insights into various aspects of the real-world entities. In this article, a predictive model is proposed using the tweets generated on Twitter social media. The proposed model calculates the potential of a topic in the tweets for the prediction purposes. The experiments were conducted on tweets of the regional election in India and the results are better than the existing systems. In the future, the model can be extended for analysis of information diffusion in heterogeneous systems.

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.

Effects of relationship types on customers’ parasocial interactions

2017 ◽  
Vol 8 (1) ◽  
pp. 133-147 ◽  
Author(s):  
Seonjeong Ally Lee ◽  
Minwoo Lee
Keyword(s):  
Social Media ◽  
Online Survey ◽  
Marketing Research ◽  
Customer Relationships ◽  
Cross Sectional ◽  
Content Type ◽  
Relationship Types ◽  
Different Types ◽  
Social Media Platforms ◽  
Parasocial Interactions

Purpose The purpose of this study is to investigate different types of customer relationships on customers’ interaction with the brand, based on prior social media and relationship marketing research. Design/methodology/approach A cross-sectional, self-administered online survey was conducted to investigate the role of different types of relationships on customers’ brand-relevant responses in the context of hotel social media platforms. Findings Results identified customers’ relationships with services and brands, and how other customers influenced their parasocial interactions (PSIs). Customers’ PSIs then positively influenced their self-brand connection and their brand usage intention. Originality/value This study was the first attempt to propose a conceptual framework to explain different types of customer relationships on customers’ interactions with the brand in the context of hotel social media platforms.

Reconciling Social Media with Luxury Fashion Brands

2015 ◽  
pp. 917-945 ◽  
Author(s):  
Wilson Ozuem ◽  
Kerri Tan
Keyword(s):  
Social Media ◽  
Information Diffusion ◽  
Cultural Transformation ◽  
Marketing Communications ◽  
Communication Media ◽  
Communications Media ◽  
Customer Expectations ◽  
Fashion Brand ◽  
Social Media Platforms ◽  
Human Association

Modern developments in communication media are creating new networks of information diffusion which are profoundly altering the way in which people can construct shared ‘realities'. Internet along with its prototypical subsets, notably social media, is enabling the emergence of new mechanism of human association which are shaped by – yet also shape – the development of this new medium of communication. This chapter integrates social media theory and luxury fashion brand theory arguments to examine the knowledge benefits that this cultural transformation provides to the development of a marketing communications programme. The authors argue that the key to providing an effective marketing communication programme is understanding and responding to customer expectations through the integration of social media platforms and traditional marketing communications media.

scholarly journals Analyzing and Visualizing Emotional Reactions Expressed by Emojis in Location-Based Social Media

2019 ◽  
Vol 8 (3) ◽  
pp. 113 ◽  
Author(s):  
Eva Hauthal ◽  
Dirk Burghardt ◽  
Alexander Dunkel
Keyword(s):  
Social Media ◽  
Emotional Reactions ◽  
Space Time ◽  
Factual Information ◽  
The Public ◽  
Different Types ◽  
Social Media Platforms

Social media platforms such as Twitter are extensively used for expressing and exchanging thoughts, opinions, ideas, and feelings, i.e., reactions concerning a topic or an event. Factual information about an event to which people are reacting can be obtained from different types of (geo-)sensors, official authorities, or the public press. However, these sources hardly reveal the emotional or attitudinal impact of events on people, which is, for example, reflected in their reactions on social media. Two approaches that utilize emojis are proposed to obtain the sentiment and emotions contained in social media reactions. Subsequently, these two approaches, along with visualizations that focus on space, time, and topic, are applied to Twitter reactions in the example case of Brexit.

Use of Multiple Social Media Platforms in Relation to Psychological Functioning in Emerging Adults

2018 ◽  
Vol 7 (6) ◽  
pp. 501-506 ◽  
Author(s):  
Anna Vannucci ◽  
Christine McCauley Ohannessian ◽  
Sonja Gagnon
Keyword(s):  
Social Media ◽  
Depressive Symptoms ◽  
Emerging Adults ◽  
Psychological Functioning ◽  
Analysis Model ◽  
Different Types ◽  
Social Media Platforms ◽  
Total Alcohol ◽  
The Relationship ◽  
Path Analysis Model

The current study examined relationships between different types of social media platforms used and psychological functioning in a diverse, national U.S. sample of emerging adults (18–22 years). Participants completed surveys online in the spring of 2014. Findings from a path analysis model suggested that individuals who used a higher number of different social media platforms reported more anxiety symptoms, depressive symptoms, total alcohol consumption, and drug use. Facebook use was associated uniquely with depressive symptoms and Snapchat use with substance use. Neither Instagram use nor Twitter use was associated with any measures of psychological functioning. Gender differences also were not observed. Findings highlight the importance of considering the number of different social media platforms used, as well as the specific platform itself, when conceptualizing the relationship between social media use and psychological functioning in emerging adults.

scholarly journals Review of Data Visualization for Social Media Postings

2018 ◽  
Vol 7 (4.38) ◽  
pp. 939
Author(s):  
Nur Atiqah Sia Abdullah ◽  
Hamizah Binti Anuar
Keyword(s):  
Social Media ◽  
Data Visualization ◽  
Line Graph ◽  
Data Types ◽  
Social Media Data ◽  
Data Analyst ◽  
The Social ◽  
Social Media Platforms ◽  
Types Of Information ◽  
Media Data

Facebook and Twitter are the most popular social media platforms among netizen. People are now more aggressive to express their opinions, perceptions, and emotions through social media platforms. These massive data provide great value for the data analyst to understand patterns and emotions related to a certain issue. Mining the data needs techniques and time, therefore data visualization becomes trending in representing these types of information. This paper aims to review data visualization studies that involved data from social media postings. Past literature used node-link diagram, node-link tree, directed graph, line graph, heatmap, and stream graph to represent the data collected from the social media platforms. An analysis by comparing the social media data types, representation, and data visualization techniques is carried out based on the previous studies. This paper critically discussed the comparison and provides a suggestion for the suitability of data visualization based on the type of social media data in hand.      

scholarly journals You're hired: examining acceptance of social media screening of job applicants

2021 ◽  
Author(s):  
Anatoliy Gruzd ◽  
Jenna Jacobson ◽  
Elizabeth Dubois
Keyword(s):  
Social Media ◽  
Online Survey ◽  
Information Privacy ◽  
Job Applicants ◽  
Comfort Level ◽  
Hiring Practices ◽  
Related Information ◽  
Different Types ◽  
Prospective Employer ◽  
Types Of Information

The paper examines attitudes towards employers using social media to screen job applicants. In an online survey of 454 participants, we compare the comfort level with this practice in relation to different types of information that can be gathered from publicly accessible social media. The results revealed a nuanced nature of people’s information privacy expectations in the context of hiring practices. People’s perceptions of employers using social media to screen job applicants depends on (1) whether or not they are currently seeking employment (or plan to), (2) the type of information that is being accessed by a prospective employer (if there are on the job market), and (3) their cultural background, but not gender. The findings emphasize the need for employers and recruiters who are relying on social media to screen job applicants to be aware of the types of information that may be perceived to be more sensitive by applicants, such as social network-related information. Keywords : social media, information privacy, job screening, hiring practices

scholarly journals Machine Learning in Detecting COVID-19 Misinformation on Twitter

2021 ◽  
Vol 13 (10) ◽  
pp. 244
Author(s):  
Mohammed N. Alenezi ◽  
Zainab M. Alqenaei
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Short Term Memory ◽  
K Nearest Neighbors ◽  
Daily Lives ◽  
Frontline Workers ◽  
Detection Model ◽  
Social Media Platforms ◽  
Long Short Term Memory ◽  
Types Of Information

Social media platforms such as Facebook, Instagram, and Twitter are an inevitable part of our daily lives. These social media platforms are effective tools for disseminating news, photos, and other types of information. In addition to the positives of the convenience of these platforms, they are often used for propagating malicious data or information. This misinformation may misguide users and even have dangerous impact on society’s culture, economics, and healthcare. The propagation of this enormous amount of misinformation is difficult to counter. Hence, the spread of misinformation related to the COVID-19 pandemic, and its treatment and vaccination may lead to severe challenges for each country’s frontline workers. Therefore, it is essential to build an effective machine-learning (ML) misinformation-detection model for identifying the misinformation regarding COVID-19. In this paper, we propose three effective misinformation detection models. The proposed models are long short-term memory (LSTM) networks, which is a special type of RNN; a multichannel convolutional neural network (MC-CNN); and k-nearest neighbors (KNN). Simulations were conducted to evaluate the performance of the proposed models in terms of various evaluation metrics. The proposed models obtained superior results to those from the literature.

scholarly journals You're hired: examining acceptance of social media screening of job applicants

2021 ◽  
Author(s):  
Anatoliy Gruzd ◽  
Jenna Jacobson ◽  
Elizabeth Dubois
Keyword(s):  
Social Media ◽  
Online Survey ◽  
Information Privacy ◽  
Job Applicants ◽  
Comfort Level ◽  
Hiring Practices ◽  
Related Information ◽  
Different Types ◽  
Prospective Employer ◽  
Types Of Information

The paper examines attitudes towards employers using social media to screen job applicants. In an online survey of 454 participants, we compare the comfort level with this practice in relation to different types of information that can be gathered from publicly accessible social media. The results revealed a nuanced nature of people’s information privacy expectations in the context of hiring practices. People’s perceptions of employers using social media to screen job applicants depends on (1) whether or not they are currently seeking employment (or plan to), (2) the type of information that is being accessed by a prospective employer (if there are on the job market), and (3) their cultural background, but not gender. The findings emphasize the need for employers and recruiters who are relying on social media to screen job applicants to be aware of the types of information that may be perceived to be more sensitive by applicants, such as social network-related information. Keywords : social media, information privacy, job screening, hiring practices

scholarly journals Researching intimacy through social media: A cross-platform approach

2016 ◽  
Vol 32 (60) ◽  
pp. 19
Author(s):  
Cristina Miguel
Keyword(s):  
Social Media ◽  
Research Design ◽  
Participant Observation ◽  
Structured Interviews ◽  
Research Project ◽  
Different Types ◽  
Social Media Platforms ◽  
Cross Platform ◽  
Media Interaction

This paper aims to contribute to the understanding of how to study the way people build intimacy and manage privacy through social media interaction. It explores the research design and methodology of a research project based on a multi-sited case study composed of three different social media platforms: Badoo, CouchSurfing, and Facebook. This cross-platform approach is useful to observe how intimacy is often negotiated across different platforms. The research project focuses on the cities of Leeds (UK) and Barcelona (Spain). In particular, this article discusses the methods used to recruit participants and collect data for that study - namely, participant observation, semi-structured interviews, and user profiles analysis. This cross-platform approach and multi-method research design is helpful to investigate the nature of intimacy practices facilitated by social media at several levels: online/offline, across different platforms, among different types of relationships, within both new and existing relationships, and in different locations

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