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 Network Analysis of COVID-19 Vaccine Misinformation on Social Media

2021 ◽  
Author(s):  
Chad Melton ◽  
Olufunto A. Olusanya ◽  
Arash Shaban-Nejad
Keyword(s):  
Social Media ◽  
Network Analysis ◽  
Semantic Network ◽  
Vaccine Safety ◽  
Vaccine Hesitancy ◽  
World Population ◽  
Semantic Network Analysis ◽  
Online Social Media ◽  
Social Media Platforms ◽  
Media Platform

Almost half of the world population has received at least one dose of vaccine against the COVID-19 virus. However, vaccine hesitancy amongst certain populations is driving new waves of infections at alarming rates. The popularity of online social media platforms attracts supporters of the anti-vaccination movement who spread misinformation about vaccine safety and effectiveness. We conducted a semantic network analysis to explore and analyze COVID-19 vaccine misinformation on the Reddit social media platform.

scholarly journals An Exploration of Impact of COVID 19 on mental health -Analysis of tweets using Natural Language Processing techniques

2020 ◽  
Author(s):  
Sohini Sengupta ◽  
Sareeta Mugde ◽  
Garima Sharma
Keyword(s):  
Mental Health ◽  
Social Media ◽  
Natural Language Processing ◽  
Natural Language ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Gold Mine ◽  
Social Media Platforms ◽  
Processing Techniques

Twitter is one of the world's biggest social media platforms for hosting abundant number of user-generated posts. It is considered as a gold mine of data. Majority of the tweets are public and thereby pullable unlike other social media platforms. In this paper we are analyzing the topics related to mental health that are recently (June, 2020) been discussed on Twitter. Also amidst the on-going pandemic, we are going to find out if covid-19 emerges as one of the factors impacting mental health. Further we are going to do an overall sentiment analysis to better understand the emotions of users.

scholarly journals Similarity approximation of Twitter Profiles

2021 ◽  
Author(s):  
Niloufar Shoeibi ◽  
Nastaran Shoeibi ◽  
Pablo Chamoso ◽  
Zakie Alizadehsani ◽  
Juan M. Corchado
Keyword(s):  
Social Media ◽  
Language Processing ◽  
User Satisfaction ◽  
Intelligent System ◽  
Media Analysis ◽  
Related Information ◽  
Social Media Platforms ◽  
Dynamic Time ◽  
Content Similarity ◽  
Processing Techniques

Social media platforms are entirely an undeniable part of the lifestyle from the past decade. Analyzing the information being shared is a crucial step to understand humans behavior. Social media analysis is aiming to guarantee a better experience for the user and risen user satisfaction. But first, it is necessary to know how and from which aspects to compare users with each other. In this paper, an intelligent system has been proposed to measure the similarity of Twitter profiles. For this, firstly, the timeline of each profile has been extracted using the official Twitter API. Then, all information is given to the proposed system. Next, in parallel, three aspects of a profile are derived. Behavioral ratios are time-series-related information showing the consistency and habits of the user. Dynamic time warping has been utilized for comparison of the behavioral ratios of two profiles. Next, Graph Network Analysis is used for monitoring the interactions of the user and its audience; for estimating the similarity of graphs, Jaccard similarity is used. Finally, for the Content similarity measurement, natural language processing techniques for preprocessing and TF-IDF for feature extraction are employed and then compared using the cosine similarity method. Results have presented the similarity level of different profiles. As the case study, people with the same interest show higher similarity. This way of comparison is helpful in many other areas. Also, it enables to find duplicate profiles; those are profiles with almost the same behavior and content.

scholarly journals Hate Speeches on Twitter and Facebook in South Asia: A Case Study Of Malala Yousufzai

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Saba Naz, Dr. Muhammad Osama Shafiq
Keyword(s):  
Social Media ◽  
South Asia ◽  
Quantitative Research ◽  
Large Scale ◽  
Hate Speech ◽  
Radical Change ◽  
Quantitative Research Methods ◽  
Social Media Platforms ◽  
Media Platform

Nowadays social media platforms have become a medium that allows people to post anything they wish. Since the time internet grew, a radical change has been discerned in society. With the emergence of social media sites, many challenges also thrived in the society that took the society into interesting and alarming ways altogether. As time is passing as technology is intensifying new forms of hate, abuse, bullying, and discrimination are also increasing in society. It can be said that digital technology is reshaping coercion based on caste, color, gender, race, culture, likes, dislikes. Many societies are concerned with this problem of growing hate speeches on social media but no proper barrier on these sites has been seen to prevent hate discourses. This study examined the attitudes of social media users including Facebook and Twitter over the incident of Noble Prize laureate Malala Yousufzai, a young activist who worked and spoke for the educational rights of girls who were born in Swat valley. She spoke against this erroneous system that didn’t allow girls to gain education and became a prominent member of society at the little age of 14. She was shot by Taliban and then a controversy started against her, some people admired her and she became a celebrity all over South Asia while an extreme amount of criticism was also seen against her incident. Through this study, we aim to understand the abundance of hate speech on Facebook and Twitter in South Asia by using Qualitative and Quantitative Research Methods. For that purpose we took the case study method and provide a large-scale measurement and analysis of different hashtags used during the case of Malala on the social media platform. To achieve the objective of our research, we amassed Tweets and Facebook posts posted since the year 2011 till now related to this case. This article identifies numerous forms of hate speeches on social media that are arising in South Asia and altering the minds of people using social media, it is also guiding how to abate hate speeches that are delivered on social media with particular hashtags on various incidents and matters. The collected data revealed that hate speech has become a social problem with substantial inimical effects in societies. This study explains that social media should be utilized to benefit mankind positively and gently.

scholarly journals Tweet Retrieval and Analysing the Trends

2021 ◽  
Vol 10 (2) ◽  
pp. 34-38
Author(s):  
Utkarsh Malik ◽  
◽  
Harpreet Kaur ◽  
Aditi Chaudhary ◽  
◽  
...  
Keyword(s):  
Social Media ◽  
Data Science ◽  
Text Processing ◽  
Political Polarization ◽  
Product Analysis ◽  
Protest Movements ◽  
Social Media Platforms ◽  
Media Platform ◽  
Processing Techniques ◽  
Share Information

We can’t disregard the importance of Social Media in Today’s Technology Era. Internet is almost in every hand. People uses various Social Media platforms to express themselves and their thinking about various topics such as Politics, Entertainment, Sports, etc. In the Data Science industry, trend analysis can be used for several purposes like marketing or product analysis. Twitter data has been used to analyze political polarization and the spread of protest movements. Twitter is one of the most popular social media platform that allows the users to spread and share information. Twitter publishes the list of recent or latest topics named as “Trending Topics” which shows all the happenings in the world and what are the people’s opinions about those topics. This Trend Analyzer will work on a given set of tweets and generates a graph based on the tweets and showsthe comparative popularity of the used hashtags. This Analyzer will examine a set of tweets using Python and text-processing techniques

scholarly journals Music Recommendation System based on Emotions in User’s Social Media behaviour

2021 ◽  
Author(s):  
Ravidu Perera
Keyword(s):  
Social Media ◽  
Language Processing ◽  
Recommendation System ◽  
Media Content ◽  
Music Recommendation ◽  
Social Media Platforms ◽  
Emotional Behaviour ◽  
Emotional Conflicts ◽  
Processing Techniques ◽  
Music Recommendation System

<p>The modern lifestyle makes people more competitive. It can lead to more stressful situations in our lifestyle. With the changes in human emotional behaviour, they tend to share their feelings on social media platforms rather than communicating with relatives. Studies proved that people used to listen to music to avoid emotional situations in their life. But there is no proper way to get the most accurate music to listen to and avoid emotional conflicts.</p> <p> </p> <p>Resolving these conflicts, the music recommendation system based on emotion introduced. It analyses the users' recent social media content and detects the various kind of emotions. To ensure that the suggested music is relevant to users emotions, the lyrics analysing was done using natural language processing techniques to identify the music emotions. Most people pay attention to the meaning of the songs, that was the major reason to consider the emotions of the lyrics.</p>

scholarly journals Adult Saudi Students’ Practices and Perceptions of Utilizing Twitter for English Language Learning in the UK

2021 ◽  
pp. 1-96
Author(s):  
Meshari Muidh Alharthi
Keyword(s):  
Social Media ◽  
Language Learning ◽  
English Language ◽  
English Language Learning ◽  
Learning Capacity ◽  
Saudi Students ◽  
The Social ◽  
Social Media Platforms ◽  
Media Platform ◽  
The Uk

Twitter is one of the most widely used social media platforms in Saudi populations; however, research is limited regarding the efficiency, practices, and perceptions of utilizing this platform for the purpose of learning English. This study investigates the ways in which adult Saudi students in the UK use Twitter to learn the English language, and assesses the general practices and perceptions of the social media platform. Employing a sequential explanatory research design by conducting questionnaire and interviews for data collection and analysis, this study reveals that there are several opportunities for English language learning through the use of Twitter. Participants consisted primarily of digital residents who use Twitter to practice and learn English, and many noted that Twitter contributes to refined different language skills and an enhanced vocabulary. Therefore, we strongly recommend that instructors and educators encourage students to use Twitter in an English language learning capacity wherever access is possible.

Music Recommendation System based on Emotions in User’s Social Media behaviour

2021 ◽  
Author(s):  
Ravidu Perera
Keyword(s):  
Social Media ◽  
Language Processing ◽  
Recommendation System ◽  
Media Content ◽  
Music Recommendation ◽  
Social Media Platforms ◽  
Emotional Behaviour ◽  
Emotional Conflicts ◽  
Processing Techniques ◽  
Music Recommendation System

<p>The modern lifestyle makes people more competitive. It can lead to more stressful situations in our lifestyle. With the changes in human emotional behaviour, they tend to share their feelings on social media platforms rather than communicating with relatives. Studies proved that people used to listen to music to avoid emotional situations in their life. But there is no proper way to get the most accurate music to listen to and avoid emotional conflicts.</p> <p> </p> <p>Resolving these conflicts, the music recommendation system based on emotion introduced. It analyses the users' recent social media content and detects the various kind of emotions. To ensure that the suggested music is relevant to users emotions, the lyrics analysing was done using natural language processing techniques to identify the music emotions. Most people pay attention to the meaning of the songs, that was the major reason to consider the emotions of the lyrics.</p>

Big Data Analytics in Social Media

2019 ◽  
pp. 107-124
Author(s):  
Janani Balakumar ◽  
Vijayarani Mohan
Keyword(s):  
Social Media ◽  
Big Data ◽  
Data Analytics ◽  
Large Scale ◽  
Rapid Development ◽  
Big Data Analytics ◽  
Information Control ◽  
Social Media Platforms ◽  
Current Scenario ◽  
Processing Techniques

The rapid development of online social media is the method of collaboratively produced content material presents new possibilities and challenges to both producers and patrons of knowledge. The term big data refers to large-scale information control and evaluation technologies that exceed the functionality of conventional data processing techniques. In the current scenario, social media has gained amazing attention within the last decade. Accessing social media platforms and websites such as Facebook, Twitter, YouTube, LinkedIn, Instagram, and Google+, web technologies have become more responsible. People are becoming more fascinated about and relying on social media platform for records, news, and opinion of other customers on diverse topics. Hence, these situations produce a large volume of data. The main objective of this chapter is to provide knowledge about big data analytics in social media. A brief overview of big data and social media are discussed. Research challenges in social media are also discussed.

Understanding the Role of Online Media Platforms in Airport Capital Projects and Community Outreach

2021 ◽  
pp. 036119812199347
Author(s):  
Max Z. Li ◽  
Megan S. Ryerson
Keyword(s):  
Social Media ◽  
Best Practices ◽  
Community Outreach ◽  
Capital Projects ◽  
The Public ◽  
Online Social Media ◽  
Social Media Platforms ◽  
Project Phases ◽  
Media Channels ◽  
Common Content

Community outreach and engagement efforts are critical to an airport’s role as an ever-evolving transportation infrastructure and regional economic driver. As online social media platforms continue to grow in both popularity and influence, a new engagement channel between airports and the public is emerging. However, the motivations behind and effectiveness of these social media channels remain unclear. In this work, we address this knowledge gap by better understanding the advantages, impact, and best practices of this newly emerging engagement channel available to airports. Focusing specifically on airport YouTube channels, we first document quantitative viewership metrics, and examine common content characteristics within airport YouTube videos. We then conduct interviews and site visits with relevant airport stakeholders to identify the motivations and workflow behind these videos. Finally, we facilitate sample focus groups designed to survey public perceptions of the effectiveness and value of these videos. From our four project phases, to maximize content effectiveness and community engagement potential, we synthesize the following framework of action items, recommendations, and best practices: (C) Consistency and community; (O) Organizational structure; (M) Momentum; (B) Branding and buy-in; (A) Activity; (T) Two-way engagement; (E) Enthusiasm; and (D) Depth, or as a convenient initialism, our COMBATED framework.

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