scholarly journals Sentiment Analysis for Fake News Detection

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1348
Author(s):  
Miguel A. Alonso ◽  
David Vilares ◽  
Carlos Gómez-Rodríguez ◽  
Jesús Vilares
Keyword(s):  
Sentiment Analysis ◽  
Well Being ◽  
Political Polarization ◽  
Text Analytics ◽  
Fake News ◽  
Huge Amount ◽  
Design And Implementation ◽  
Near Future ◽  
Manual Verification ◽  
Automatic Systems

In recent years, we have witnessed a rise in fake news, i.e., provably false pieces of information created with the intention of deception. The dissemination of this type of news poses a serious threat to cohesion and social well-being, since it fosters political polarization and the distrust of people with respect to their leaders. The huge amount of news that is disseminated through social media makes manual verification unfeasible, which has promoted the design and implementation of automatic systems for fake news detection. The creators of fake news use various stylistic tricks to promote the success of their creations, with one of them being to excite the sentiments of the recipients. This has led to sentiment analysis, the part of text analytics in charge of determining the polarity and strength of sentiments expressed in a text, to be used in fake news detection approaches, either as a basis of the system or as a complementary element. In this article, we study the different uses of sentiment analysis in the detection of fake news, with a discussion of the most relevant elements and shortcomings, and the requirements that should be met in the near future, such as multilingualism, explainability, mitigation of biases, or treatment of multimedia elements.

scholarly journals [Ir]rationality, Happiness, and Benefit-Cost Analysis: Introduction to the Special Issue

2016 ◽  
Vol 7 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Lisa A. Robinson
Keyword(s):  
Cost Analysis ◽  
Behavioral Economics ◽  
Policy Design ◽  
Well Being ◽  
Special Issue ◽  
Benefit Cost Analysis ◽  
Design And Implementation ◽  
Societal Welfare ◽  
Benefit Cost ◽  
The Relationship

Behavioral economics and happiness research have many important implications for the conduct of benefit-cost analysis as well as for policy design and implementation. By identifying ways in which we may act irrationally and providing new perspectives on the relationship between our circumstances and our sense of well-being, this research raises numerous questions regarding the evaluation of individual and societal welfare and the desirability of alternative policies. In this special issue, we present a series of articles that explore these concerns and provide significant new insights.

scholarly journals Novel Immunotherapeutic Approaches for Neuroblastoma and Malignant Melanoma

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Fabio Morandi ◽  
Francesco Frassoni ◽  
Mirco Ponzoni ◽  
Chiara Brignole
Keyword(s):  
Malignant Melanoma ◽  
Age Of Onset ◽  
Treatment Options ◽  
Treatment Strategies ◽  
Biological Knowledge ◽  
Huge Amount ◽  
High Stage ◽  
New Treatment ◽  
Near Future ◽  
Primary Tissue

Neuroblastoma (NB) and malignant melanoma (MM), tumors of pediatric age and adulthood, respectively, share a common origin, both of them deriving from the neural crest cells. Although NB and MM have a different behavior, in respect to age of onset, primary tissue involvement and metastatic spread, the prognosis for high stage-affected patients is still poor, in spite of aggressive treatment strategies and the huge amount of new discovered biological knowledge. For these reasons researchers are continuously attempting to find out new treatment options, which in a near future could be translated to the clinical practice. In the last two decades, a strong effort has been spent in the field of translational research of immunotherapy which led to satisfactory results. Indeed, several immunotherapeutic clinical trials have been performed and some of them also resulted beneficial. Here, we summarize preclinical studies based on immunotherapeutic approaches applied in models of both NB and MM.

scholarly journals Fake news, fast and slow: Deliberation reduces belief in false (but not true) news headlines

2019 ◽  
Author(s):  
Bence Bago ◽  
David Gertler Rand ◽  
Gordon Pennycook
Keyword(s):  
Political Ideology ◽  
Time Pressure ◽  
Memory Load ◽  
Causal Effect ◽  
Political Polarization ◽  
Fake News ◽  
System 2 ◽  
False News ◽  
News Headlines ◽  
Classical Account

What role does deliberation play in susceptibility to political misinformation and “fake news”? The “Motivated System 2 Reasoning” account posits that deliberation causes people to fall for fake news because reasoning facilitates identity-protective cognition and is therefore used to rationalize content that is consistent with one’s political ideology. The classical account of reasoning instead posits that people ineffectively discern between true and false news headlines when they fail to deliberate (and instead rely on intuition). To distinguish between these competing accounts, we investigated the causal effect of reasoning on media truth discernment using a two-response paradigm. Participants (N= 1635 MTurkers) were presented with a series of headlines. For each, they were first asked to give an initial, intuitive response under time pressure and concurrent working memory load. They were then given an opportunity to re-think their response with no constraints, thereby permitting more deliberation. We also compared these responses to a (deliberative) one-response baseline condition where participants made a single choice with no constraints. Consistent with the classical account, we found that deliberation corrected intuitive mistakes: subjects believed false headlines (but not true headlines) more in initial responses than in either final responses or the unconstrained 1-response baseline. In contrast – and inconsistent with the Motivated System 2 Reasoning account – we found that political polarization was equivalent across responses. Our data suggest that, in the context of fake news, deliberation facilitates accurate belief formation and not partisan bias.

scholarly journals A Survey on Analysis of Twitter Opinion Mining Using Sentiment Analysis

2019 ◽  
pp. 537-542
Author(s):  
Vishnu VardanReddy ◽  
Mahesh Maila ◽  
Sai Sri Raghava ◽  
Yashwanth Avvaru ◽  
Sri. V. Koteswarao
Keyword(s):  
Social Networking ◽  
Sentiment Analysis ◽  
Social Networking Sites ◽  
Opinion Mining ◽  
Online Communication ◽  
Valuable Insight ◽  
Huge Amount ◽  
Twitter Data ◽  
Product Service ◽  
Different Types

In recent years, there is a rapid growth in online communication. There are many social networking sites and related mobile applications, and some more are still emerging. Huge amount of data is generated by these sites everyday and this data can be used as a source for various analysis purposes. Twitter is one of the most popular networking sites with millions of users. There are users with different views and varieties of reviews in the form of tweets are generated by them. Nowadays Opinion Mining has become an emerging topic of research due to lot of opinionated data available on Blogs & social networking sites. Tracking different types of opinions & summarizing them can provide valuable insight to different types of opinions to users who use Social networking sites to get reviews about any product, service or any topic. Analysis of opinions & its classification on the basis of polarity (positive, negative, neutral) is a challenging task. Lot of work has been done on sentiment analysis of twitter data and lot needs to be done. In this paper we discuss the levels, approaches of sentiment analysis, sentiment analysis of twitter data, existing tools available for sentiment analysis and the steps involved for same. Two approaches are discussed with an example which works on machine learning and lexicon based respectively.

scholarly journals Loodus tuleb tagasi: delfiinid ja saurused. Libauudistest, photoshop-muistenditest ja meemidest koroonakarantiini ajal

Mäetagused ◽  
2021 ◽  
Vol 79 ◽  
pp. 167-184
Author(s):  
Eda Kalmre ◽  
Keyword(s):  
Social Media ◽  
Coping Strategies ◽  
Well Being ◽  
Point Of View ◽  
Human Existence ◽  
The Other ◽  
Fake News ◽  
The Social ◽  
Truth Value ◽  
Positive Effect

The article follows the narrative trend initiated by the social media posts and fake news during the first months of the corona quarantine, which claims that the decrease of contamination due to the quarantine has a positive effect on the environment and nature recovery. The author describes the context of the topic and follows the changes in the rhetoric through different genres, discussing the ways in which a picture can tell a truthful story. What is the relation between the context, truth, and rhetoric? This material spread globally, yet it was also readily “translated” into the Estonian context, and – what is very characteristic of the entire pandemic material – when approaching this material, truthful and fabricated texts, photos, and videos were combined. From the folkloristic point of view, these rumours in the form of fake news, first presented in the function of a tall tale and further following the sliding truth scale of legends, constitute a part of coping strategies, so-called crisis humour, yet, on the other hand, also a belief story presenting positive imagery, which surrounds the mainly apocalyptically perceived pandemic period and interprets the human existence on a wider scale. Even if these fake news and memes have no truth value, they communicate an idea – nature recovers – and definitely offer hope and a feeling of well-being.

scholarly journals An Analysis of Fake Narratives on Social Media during 2019 Indonesian Presidential Election

2020 ◽  
Vol 36 (4) ◽  
pp. 351-368
Author(s):  
Vience Mutiara Rumata ◽  
◽  
Fajar Kuala Nugraha ◽  
Keyword(s):  
Social Media ◽  
Presidential Election ◽  
Political Polarization ◽  
Political Discussion ◽  
Fake News ◽  
Data Set ◽  
Political Situation ◽  
Radical Group ◽  
Time Frames ◽  
Election Studies

Social media become a public sphere for political discussion in the world, with no exception in Indonesia. Social media have broadened public engagement but at the same time, it creates an inevitable effect of polarization particularly during the heightened political situation such as a presidential election. Studies found that there is a correlation between fake news and political polarization. In this paper, we identify and the pattern of fake narratives in Indonesia in three different time frames: (1) the Presidential campaign (23 September 2018 -13 April 2019); (2) the vote (14-17 April 2019); (3) the announcement (21-22 May 2019). We extracted and analyzed a data-set consisting of 806,742 Twitter messages, 143 Facebook posts, and 16,082 Instagram posts. We classified 43 fake narratives where Twitter was the most used platform to distribute fake narratives massively. The accusation of Muslim radical group behind Prabowo and Communist accusation towards the incumbent President Joko Widodo were the two top fake narratives during the campaign on Twitter and Facebook. The distribution of fake narratives to Prabowo was larger than that to Joko Widodo on those three platforms in this period. On the contrary, the distribution of fake narratives to Joko Widodo was significantly larger than that to Prabowo during the election and the announcement periods. The death threat of Joko Widodo was top fake narratives on these three platforms. Keywords: Fake narratives, Indonesian presidential election, social media, political polarization, post.

scholarly journals Meeting the challenge of (co-)designing real-world laboratories: Insights from the Well-Being Transformation Wuppertal project

2020 ◽  
Vol 29 (3) ◽  
pp. 154-160 ◽  
Author(s):  
Michael Rose ◽  
Katrin Maibaum
Keyword(s):  
Real World ◽  
Well Being ◽  
Lessons Learned ◽  
Design Phase ◽  
Structured Interviews ◽  
Project Proposal ◽  
Management Communication ◽  
Design And Implementation ◽  
Project Documentation ◽  
Organisational Structures

As transdisciplinary and transformative research approaches, real-world laboratories (RwLs) come with many pitfalls. Their design and implementation place high demands on everyone involved, which means that realistically, things rarely go smoothly. The following Design Report shares the lessons learned about establishing and adjusting communication and organisational structures in RwLs.What should we take into account when setting up real-world laboratories (RwLs)? In our analysis of the experience of (co-)designing three RwLs within the Well-Being Transformation Wuppertal research project, we examine both the origin of the project proposal and its implementation, from management, communication and inter- and transdisciplinarity to actor dynamics and recruitment criteria for staff. We especially highlight the effects of the initial co-design phase (project proposal) on the RwL’s implementation, focusing on the challenges which arose and how these were addressed.We conducted 19 semi-structured interviews, analysed relevant project documentation and reflected on the research team’s own experiences. The transdisciplinary and transformative dimensions of the RwL approach are the areas where significant lessons were learned. RwLs are unique in their extraordinarily strong need to balance different roles and resources, even as many of their challenges and solutions resemble those which also arise in transdisciplinary research. The uniqueness of RwLs lies in their objective to co-produce not only socially robust knowledge but also tangible real-world change through experimentation.

scholarly journals The Power of Social Media Analytics: Text Analytics Based on Sentiment Analysis and Word Clouds on R

2018 ◽  
Vol 22 (1/2018) ◽  
pp. 25-38
Author(s):  
Ahmed Imran KABIR ◽  
Ridoan KARIM ◽  
Shah NEWAZ ◽  
Muhammad Istiaque HOSSAIN
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Social Media Analytics ◽  
Text Analytics ◽  
Word Clouds

Sentiment Analysis with Social Media Analytics, Methods, Process, and Applications

2017 ◽  
pp. 192-208
Author(s):  
Karteek Ramalinga Ponnuru ◽  
Rashik Gupta ◽  
Shrawan Kumar Trivedi
Keyword(s):  
Social Media ◽  
Support Vector Machine ◽  
Sentiment Analysis ◽  
Support Vector ◽  
Social Media Analytics ◽  
Nearest Neighbour ◽  
Huge Amount ◽  
Word Clouds

Firms are turning their eye towards social media analytics to get to know what people are really talking about their firm or their product. With the huge amount of buzz being created online about anything and everything social media has become ‘the' platform of the day to understand what public on a whole are talking about a particular product and the process of converting all the talking into valuable information is called Sentiment Analysis. Sentiment Analysis is a process of identifying and categorizing a piece of text into positive or negative so as to understand the sentiment of the users. This chapter would take the reader through basic sentiment classifiers like building word clouds, commonality clouds, dendrograms and comparison clouds to advanced algorithms like K Nearest Neighbour, Naïve Biased Algorithm and Support Vector Machine.

Combating Fake News Online

2020 ◽  
pp. 273-289
Author(s):  
Mehmet Fatih Çömlekçi
Keyword(s):  
Content Analysis ◽  
Digital Literacy ◽  
Digital Tools ◽  
Political Polarization ◽  
Fake News ◽  
Depth Interview ◽  
Rapid Spread ◽  
Data Journalism ◽  
Fact Checking ◽  
Methodological Approaches

In today's post-truth environment, besides the increase in political polarization, the rapid spread of fake news infringes on society. In the struggle with fake news, fact-checking services have begun to play an important role. The aim of this chapter is to highlight how fact-checking services work, what their strategies and limitations are, their interaction with users, and the digital tools they use in such interactions. Thus, the platforms Teyit.org (Confirmation) and Doğruluk Payı (Share of Truth) that operate in Turkey have been chosen as exemplary cases. In the study, the content analysis and the in-depth interview methodological approaches have been used together. As a conclusion, it has been revealed that these aforementioned fact-checking services increase their activities during election times, adopt the principles of political impartiality and economic transparency, use the practices of data journalism, interact with users, and try to create a digital literacy ecosystem as an ultimate goal.

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