scholarly journals Evaluating Cultural Impact in Discursive Space through Digital Footprints

2021 ◽  
Vol 13 (7) ◽  
pp. 4043 ◽  
Author(s):  
Jesús López Baeza ◽  
Jens Bley ◽  
Kay Hartkopf ◽  
Martin Niggemann ◽  
James Arias ◽  
...  
Keyword(s):  
Social Media ◽  
Language Processing ◽  
Social Activity ◽  
Test Site ◽  
Cultural Discourse ◽  
Discursive Space ◽  
Topic Identification ◽  
Small Test ◽  
The Impact ◽  
The City

The research presented in this paper describes an evaluation of the impact of spatial interventions in public spaces, measured by social media data. This contribution aims at observing the way a spatial intervention in an urban location can affect what people talk about on social media. The test site for our research is Domplatz in the center of Hamburg, Germany. In recent years, several actions have taken place there, intending to attract social activity and spotlight the square as a landmark of cultural discourse in the city of Hamburg. To evaluate the impact of this strategy, textual data from the social networks Twitter and Instagram (i.e., tweets and image captions) are collected and analyzed using Natural Language Processing intelligence. These analyses identify and track the cultural topic or “people talking about culture” in the city of Hamburg. We observe the evolution of the cultural topic, and its potential correspondence in levels of activity, with certain intervention actions carried out in Domplatz. Two analytic methods of topic clustering and tracking are tested. The results show a successful topic identification and tracking with both methods, the second one being more accurate. This means that it is possible to isolate and observe the evolution of the city’s cultural discourse using NLP. However, it is shown that the effects of spatial interventions in our small test square have a limited local scale, rather than a city-wide relevance.

scholarly journals Social media: an exploration of the outcomes of social media use for homeless youth

2021 ◽  
Author(s):  
Jennifer Donath
Keyword(s):  
Social Media ◽  
Young Adults ◽  
Mobile Device ◽  
Homeless Youth ◽  
Qualitative Interviews ◽  
Daily Basis ◽  
Future Research ◽  
The Internet ◽  
The Impact ◽  
The City

The purpose of this project was to explore how young adults are experiencing relationships when using social media. Using a qualitative design young adults between the ages of 16-25 were asked questions about their experience with social media in the city of Toronto. Qualitative interviews were conducted with three homeless participants who used social media and had access to the internet and a mobile device. The researcher analyzed the data by looking for themes within the participant’s answers. Discussion focuses on the impact of social media, their experiences as a homeless youth and the interaction with social media on a daily basis. The findings also suggest future research for technology amongst homeless youth

scholarly journals New explainability method for BERT-based model in fake news detection

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mateusz Szczepański ◽  
Marek Pawlicki ◽  
Rafał Kozik ◽  
Michał Choraś
Keyword(s):  
Artificial Intelligence ◽  
Social Media ◽  
Language Processing ◽  
High Performance ◽  
Real Life ◽  
Contemporary Society ◽  
Fake News ◽  
Interpretable Model ◽  
Deep Integration ◽  
The Impact

AbstractThe ubiquity of social media and their deep integration in the contemporary society has granted new ways to interact, exchange information, form groups, or earn money—all on a scale never seen before. Those possibilities paired with the widespread popularity contribute to the level of impact that social media display. Unfortunately, the benefits brought by them come at a cost. Social Media can be employed by various entities to spread disinformation—so called ‘Fake News’, either to make a profit or influence the behaviour of the society. To reduce the impact and spread of Fake News, a diverse array of countermeasures were devised. These include linguistic-based approaches, which often utilise Natural Language Processing (NLP) and Deep Learning (DL). However, as the latest advancements in the Artificial Intelligence (AI) domain show, the model’s high performance is no longer enough. The explainability of the system’s decision is equally crucial in real-life scenarios. Therefore, the objective of this paper is to present a novel explainability approach in BERT-based fake news detectors. This approach does not require extensive changes to the system and can be attached as an extension for operating detectors. For this purposes, two Explainable Artificial Intelligence (xAI) techniques, Local Interpretable Model-Agnostic Explanations (LIME) and Anchors, will be used and evaluated on fake news data, i.e., short pieces of text forming tweets or headlines. This focus of this paper is on the explainability approach for fake news detectors, as the detectors themselves were part of previous works of the authors.

scholarly journals ‘Digital Citizens’: Political Participation of Russian Youth Online

2021 ◽  
pp. 143-155
Author(s):  
Roman Pyrma
Keyword(s):  
Social Media ◽  
Political Participation ◽  
Large Scale ◽  
Online Survey ◽  
Social Activity ◽  
Political Activity ◽  
Political Aspect ◽  
The Status ◽  
Combination Of Methods ◽  
The Impact

The study contributes to defining the impact of digital communication on civic and political participation, explaining how social media mediate public activism. Based on the concept of the ‘digital citizenship’ the paper reveals the political aspect of the public activism of Russian youth online. The empirical model is based on a combination of methods and procedures of applied research in order to reveal the details of civil and political participation, and protest activism of youth online. The research model includes analysis of social media and a large-scale online survey of the younger audience. Based on the analysis of social media information flows, the paper states the prevalence of the youth’s civic participation over political participation, as well as the fact that the dynamics of social activity depend on the events and the current agenda. The authors describe the level of civic and political activity of youth online based on sociological data. They also divide the audience of the protest theatre according to the following models: leaders, activists, followers, and spectators. In general, the study reveals the status and details of the younger generation’s communication activity online, where communities establish and implications of linking actions appear.

scholarly journals Bots are less central than verified accounts during contentious political events

2021 ◽  
Vol 118 (11) ◽  
pp. e2013443118
Author(s):  
Sandra González-Bailón ◽  
Manlio De Domenico
Keyword(s):  
Social Media ◽  
Language Processing ◽  
Information Campaigns ◽  
Online Networks ◽  
The Public ◽  
News Sources ◽  
Diffusion Structure ◽  
Political Events ◽  
Information Manipulation ◽  
The Impact

Information manipulation is widespread in today’s media environment. Online networks have disrupted the gatekeeping role of traditional media by allowing various actors to influence the public agenda; they have also allowed automated accounts (or bots) to blend with human activity in the flow of information. Here, we assess the impact that bots had on the dissemination of content during two contentious political events that evolved in real time on social media. We focus on events of heightened political tension because they are particularly susceptible to information campaigns designed to mislead or exacerbate conflict. We compare the visibility of bots with human accounts, verified accounts, and mainstream news outlets. Our analyses combine millions of posts from a popular microblogging platform with web-tracking data collected from two different countries and timeframes. We employ tools from network science, natural language processing, and machine learning to analyze the diffusion structure, the content of the messages diffused, and the actors behind those messages as the political events unfolded. We show that verified accounts are significantly more visible than unverified bots in the coverage of the events but also that bots attract more attention than human accounts. Our findings highlight that social media and the web are very different news ecosystems in terms of prevalent news sources and that both humans and bots contribute to generate discrepancy in news visibility with their activity.

scholarly journals A Hybrid Deep Learning Model to Predict the Impact of COVID-19 on Mental Health form Social Media Big Data

2021 ◽  
Author(s):  
Tapotosh Ghosh ◽  
Md. Hasan Al Banna ◽  
Md. Jaber Al Nahian ◽  
Kazi Abu Taher ◽  
M Shamim Kaiser ◽  
...  
Keyword(s):  
Neural Network ◽  
Mental Health ◽  
Social Media ◽  
Big Data ◽  
Language Processing ◽  
Short Term Memory ◽  
Daily Basis ◽  
Significant Rise ◽  
Special Focus ◽  
The Impact

The novel coronavirus disease (COVID-19) pandemic is provoking a prevalent consequence on mental health because of less interaction among people, economic collapse, negativity, fear of losing jobs, and death of the near and dear ones. To express their mental state, people often are using social media as one of the preferred means. Due to reduced outdoor activities, people are spending more time on social media than usual and expressing their emotion of anxiety, fear, and depression. On a daily basis, about 2.5 quintillion bytes of data are generated on social media, analyzing this big data can become an excellent means to evaluate the effect of COVID-19 on mental health. In this work, we have analyzed data from Twitter microblog (tweets) to find out the effect of COVID-19 on peoples mental health with a special focus on depression. We propose a novel pipeline, based on recurrent neural network (in the form of long-short term memory or LSTM) and convolutional neural network, capable of identifying depressive tweets with an accuracy of 99.42%. Preprocessed using various natural language processing techniques, the aim was to find out depressive emotion from these tweets. Analyzing over 571 thousand tweets posted between October 2019 and May 2020 by 482 users, a significant rise in depressing tweets was observed between February and May of 2020, which indicates as an impact of the long ongoing COVID-19 pandemic situation.

scholarly journals ‘Mobile Phones and the Internet, Mate’: (Social) Media, Art, and Revolution in Omar Robert Hamilton’s The City Always Wins

Humanities ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 86
Author(s):  
Claire Chambers
Keyword(s):  
Social Media ◽  
Real Life ◽  
The Internet ◽  
Citizen Journalism ◽  
Egyptian Revolution ◽  
Non Profit ◽  
History Of ◽  
Experimental Novel ◽  
The Impact ◽  
The City

In his novel about the Egyptian Revolution, The City Always Wins (2017), Omar Robert Hamilton shows that the alternative media possess mass engagement and global reach, while threatening power. However, over the course of his novel Hamilton traces the crushing of the ‘Twitter revolution’ and the rise of a disillusionment and despair among the revolutionaries. This downward trajectory is typified both in the appellative journey from Hamilton’s non-profit media collective Mosireen—‘those who insist’—to the novel’s similar group, portentously named Chaos; and in the text’s reverse-chronological structure of ‘Tomorrow’, ‘Today’, and ‘Yesterday’. The author uses Twitter as an archive of an alternative, resistant history of revolutionary struggle; he embeds Tweets in the fabric of this experimental novel; and social media posts interrupt and punctuate the narrative as in the real life of his millennial characters. In this article I explore the novel’s representations of (social) media and the impact these have both on everyday lives and modes of protest. Despite promising beginnings, the internet ultimately turns ‘toxic’ and is depicted as a Pandora’s box of dis- and misinformation, conspiracy theories, fake news, and the manipulations of state media lackeys. A more lasting alternative to media may be ‘creative insurgency’. As such, I conclude this article by discussing what art can achieve that (citizen) journalism cannot, and how this applies to the novel’s portrayals of art, particularly music.

scholarly journals Social Activity in Gothenburg’s Intermediate City: Mapping Third Places through Social Media Data

2020 ◽  
Vol 13 (4) ◽  
pp. 985-1017
Author(s):  
Marco Adelfio ◽  
Leticia Serrano-Estrada ◽  
Pablo Martí-Ciriquián ◽  
Jaan-Henrik Kain ◽  
Jenny Stenberg
Keyword(s):  
Social Media ◽  
Urban Areas ◽  
Social Life ◽  
Social Activity ◽  
Third Places ◽  
Social Media Data ◽  
The City ◽  
Media Data ◽  
Urban Activity ◽  
Activity Areas

Abstract This research focuses on the intermediate city, composed of urban areas located right outside the city center typically maintaining an in-between urban/suburban character. It aims to explore the degree to which this segment of the city exhibits urban activity and social life through the identification of activity areas in the so-called Third Places. Four intermediate city neighborhoods in Gothenburg, Sweden are adopted as case areas and are analyzed using a twofold approach. First, socio-economic statistics provide a quantitative understanding of the case areas and, second, geolocated Social Media Data (SMD) from Foursquare, Google Places and Twitter makes it possible to identify the intermediate city’s urban activity areas and socially preferred urban spaces. The findings suggest that a) the four analyzed intermediate city areas of Gothenburg all have a degree of social activity, especially where economic activities are clustered together; b) Third Places in more affluent areas tend to be linked to commodified consumption of urban space while neighborhoods with lower income levels and higher ethnic diversity seem to emphasize open public space as Third Places; and c) nowadays the typology of Third Places has evolved from the types identified in previous decades to include additional types of places, such as those you pass on the way to something else (e.g. gas and bus stations). The study has verified the value of SMD for studies of urban social life but also identified a number of topics for further research. Additional sources of SMD should be identified to secure a just representation of Third Places across diverse social groups. Furthermore, new methods for effective cross validation of SMD with other types of data are crucial, including e.g. statistics, on-site observations and surveys/interviews, not least to identify Third Places that are not frequently present (or are misrepresented) in SMD.

scholarly journals Health, Psychosocial, and Social issues emanating from COVID-19 pandemic based on Social Media Comments using Natural Language Processing (Preprint)

2020 ◽  
Author(s):  
Oladapo Oyebode ◽  
Chinenye Ndulue ◽  
Ashfaq Adib ◽  
Dinesh Mulchandani ◽  
Banuchitra Suruliraj ◽  
...  
Keyword(s):  
Social Media ◽  
Natural Language Processing ◽  
Language Processing ◽  
Social Issues ◽  
Public Perceptions ◽  
Psychosocial Issues ◽  
Social Media Data ◽  
Health Related ◽  
The Impact ◽  
Media Data

BACKGROUND The COVID-19 pandemic has caused a global health crisis that affects many aspects of human lives. In the absence of vaccines and antivirals, several behavioural change and policy initiatives, such as physical distancing, have been implemented to control the spread of the coronavirus. Social media data can reveal public perceptions toward how governments and health agencies across the globe are handling the pandemic, as well as the impact of the disease on people regardless of their geographic locations in line with various factors that hinder or facilitate the efforts to control the spread of the pandemic globally. OBJECTIVE This paper aims to investigate the impact of the COVID-19 pandemic on people globally using social media data. METHODS We apply natural language processing (NLP) and thematic analysis to understand public opinions, experiences, and issues with respect to the COVID-19 pandemic using social media data. First, we collect over 47 million COVID-19-related comments from Twitter, Facebook, YouTube, and three online discussion forums. Second, we perform data preprocessing which involves applying NLP techniques to clean and prepare the data for automated theme extraction. Third, we apply context-aware NLP approach to extract meaningful keyphrases or themes from over 1 million randomly-selected comments, as well as compute sentiment scores for each theme and assign sentiment polarity (i.e., positive, negative, or neutral) based on the scores using lexicon-based technique. Fourth, we categorize related themes into broader themes. RESULTS A total of 34 negative themes emerged, out of which 15 are health-related issues, psychosocial issues, and social issues related to the COVID-19 pandemic from the public perspective. Some of the health-related issues are increased mortality, health concerns, struggling health systems, and fitness issues; while some of the psychosocial issues include frustrations due to life disruptions, panic shopping, and expression of fear. Social issues include harassment, domestic violence, and wrong societal attitude. In addition, 20 positive themes emerged from our results. Some of the positive themes include public awareness, encouragement, gratitude, cleaner environment, online learning, charity, spiritual support, and innovative research. CONCLUSIONS We uncover various negative and positive themes representing public perceptions toward the COVID-19 pandemic and recommend interventions that can help address the health, psychosocial, and social issues based on the positive themes and other remedial ideas rooted in research. These interventions will help governments, health professionals and agencies, institutions, and individuals in their efforts to curb the spread of COVID-19 and minimize its impact, as well as in reacting to any future pandemics.

scholarly journals Approach for social media content-based analysis for vacation resorts

2019 ◽  
Vol 15 (3) ◽  
Author(s):  
Snezhana Sulova ◽  
Boris Bankov
Keyword(s):  
Social Media ◽  
Language Processing ◽  
Text Processing ◽  
Automated Analysis ◽  
New Approach ◽  
Useful Knowledge ◽  
Media Messages ◽  
Customer Feedback ◽  
Processing Techniques ◽  
The Impact

The impact of social networks on our liveskeeps increasing because they provide content,generated and controlled by users, that is constantly evolving. They aid us in spreading news, statements, ideas and comments very quickly. Social platforms are currently one of the richest sources of customer feedback on a variety of topics. A topic that is frequently discussed is the resort and holiday villages and the tourist services offered there. Customer comments are valuable to both travel planners and tour operators. The accumulation of opinions in the web space is a prerequisite for using and applying appropriate tools for their computer processing and for extracting useful knowledge from them. While working with unstructured data, such as social media messages, there isn’t a universal text processing algorithm because each social network and its resources have their own characteristics. In this article, we propose a new approach for an automated analysis of a static set of historical data of user messages about holiday and vacation resorts, published on Twitter. The approach is based on natural language processing techniques and the application of machine learning methods. The experiments are conducted using softwareproduct RapidMiner. 

scholarly journals Social media: an exploration of the outcomes of social media use for homeless youth

2021 ◽  
Author(s):  
Jennifer Donath
Keyword(s):  
Social Media ◽  
Young Adults ◽  
Mobile Device ◽  
Homeless Youth ◽  
Qualitative Interviews ◽  
Daily Basis ◽  
Future Research ◽  
The Internet ◽  
The Impact ◽  
The City

The purpose of this project was to explore how young adults are experiencing relationships when using social media. Using a qualitative design young adults between the ages of 16-25 were asked questions about their experience with social media in the city of Toronto. Qualitative interviews were conducted with three homeless participants who used social media and had access to the internet and a mobile device. The researcher analyzed the data by looking for themes within the participant’s answers. Discussion focuses on the impact of social media, their experiences as a homeless youth and the interaction with social media on a daily basis. The findings also suggest future research for technology amongst homeless youth

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