Tracking the History and Evolution of Entities: Entity-centric Temporal Analysis of Large Social Media Archives

How did the popularity of the Greek Prime Minister evolve in 2015? How did the predominant sentiment about him vary during that period? Were there any controversial sub-periods? What other entities were related to him during these periods? To answer these questions, one needs to analyze archived documents and data about the query entities, such as old news articles or social media archives. In particular, user-generated content posted in social networks, like Twitter and Facebook, can be seen as a comprehensive documentation of our society, and thus meaningful analysis methods over such archived data are of immense value for sociologists, historians and other interested parties who want to study the history and evolution of entities and events. To this end, in this paper we propose an entity-centric approach to analyze social media archives and we define measures that allow studying how entities were reflected in social media in different time periods and under different aspects, like popularity, attitude, controversiality, and connectedness with other entities. A case study using a large Twitter archive of four years illustrates the insights that can be gained by such an entity-centric and multi-aspect analysis.Comment: This is a preprint of an article accepted for publication in the International Journal on Digital Libraries (2018

Viewpoint Discovery and Understanding in Social Networks

The Web has evolved to a dominant platform where everyone has the opportunity to express their opinions, to interact with other users, and to debate on emerging events happening around the world. On the one hand, this has enabled the presence of different viewpoints and opinions about a - usually controversial - topic (like Brexit), but at the same time, it has led to phenomena like media bias, echo chambers and filter bubbles, where users are exposed to only one point of view on the same topic. Therefore, there is the need for methods that are able to detect and explain the different viewpoints. In this paper, we propose a graph partitioning method that exploits social interactions to enable the discovery of different communities (representing different viewpoints) discussing about a controversial topic in a social network like Twitter. To explain the discovered viewpoints, we describe a method, called Iterative Rank Difference (IRD), which allows detecting descriptive terms that characterize the different viewpoints as well as understanding how a specific term is related to a viewpoint (by detecting other related descriptive terms). The results of an experimental evaluation showed that our approach outperforms state-of-the-art methods on viewpoint discovery, while a qualitative analysis of the proposed IRD method on three different controversial topics showed that IRD provides comprehensive and deep representations of the different viewpoints

Introduction—What is Epistemic Contextualism?

Introduces contextualism about knowledge ascriptions, and provides a brief summary of the contributions to the Routledge Handbook of Epistemic Contextualism

CRITICAL DISCOURSE ANALYSIS IN DONALD TRUMP’S TERRORISM NATIONAL SECURITY SPEECH

ABSTRACT CRITICAL DISCOURSE ANALYSIS IN DONALD TRUMP’S TERRORISM NATIONAL SECURITY SPEECH BY : YUNITA AMELIA NURDAMAYANTI This study examines Donald Trump‟s Terrorism National Security Speech by using Critical Discourse Analysis (CDA) Theory of Van Dijk. This study investigate the structures of Critical Discourse Analysis that arise in Donald Trump Terrorism National Security Speech which consist of three structures of analysis consisting of macrostructure, microstructure, and superstructure. This study used the descriptive qualitative method, which deals with data in the form of words and attempts to arrive at a detailed description of something systematically. The data were collected online on livenow from the FOX Youtube channel. The result of the study, the writer found the power and ideology in the Trump‟s speech . In his speech, he consistently uses irony to involve emotional attachment to the intended. The use of repetition is largely conveyed about the past failures, this strategy aims to attack the recipients attention and persuade to agree with the arguments using logical facts and emotional attachment. Furthermore, this research contributes to the understanding of Critical Discourse Analysis and how it functions in studying various social issues. Keywords : Critical Discourse Analysis, Donald Trump Speech, Discourse Structures, Attachmen

(UN)WELCOME TO AMERICA: A CRITICAL DISCOURSE ANALYSIS OF ANTI-IMMIGRANT RHETORIC IN TRUMP’S SPEECHES AND CONSERVATIVE MAINSTREAM MEDIA

This project makes the empirical assertion that U.S. President Donald Trump and conservative news media outlets contribute to a national narrative of xenophobia that frames immigrants, particularly those of color, as parasitic and dangerous to the American way of life. Through this study, I assert that the use of demagogic and dehumanizing language along with more subtle discursive strategies, such as positive representation of ‘us’, negative representation of ‘them,’ and metaphorical constructions are being used to stoke fear and anti-immigrant sentiment and to strip individuals of their humanity for the purpose of rendering them unworthy of dignity and of the same rights and benefits as those to which groups considered insiders and ‘real Americans’ are entitled. Through the lens of Critical Discourse Analysis and Corpus Linguistics, I analyze a collection of transcriptions selected from among 100+ speeches, addresses and remarks delivered by Donald Trump both before and after the 2016 U.S. Presidential Elections, along with a set of ten news stories featuring issues surrounding immigration collected from FoxNews.com, Breitbart.com, and Bill O’Reilly.com. Concordancing software is used to reveal and quantify discursive patterns that contribute to this national narrative of xenophobia

EQUIVALENCE IN NEWS HEADLINESTRANSLATION: ENGLISH HEADLINES RENDERED INTO BAHASA INDONESIA IN BBC WEB NEWS

Equivalence is the leading subject in translation studies; hence, a wide range of hypotheses on equivalence have been discussed in detail within this field translation over the recent decades. Equivalence in translation is influenced by many different factors, i.e., parts of importance among words and articulations, language structure and participants in various communicative circumstances, semantics, pragmatics, etc. The concept of equivalence with the focus on equivalence degrees is provided; the overview and characterization of the main features, as well as specifics of translation of media language (headlines in particular), are presented in the article as well. The paper focuses on the equivalence in the translation of headlines of on-line news articles since headlines are considered as crucial and the most important part of news articles. The translation of news headlines across certain journalistic cultures, specifically focusing on headlines translated from English into Bahasa Indonesia. Headlines are an extraordinary type of text, which are considered a separate genre on their own. Since a headline is an entrance to the news details, journalists have to utilize different techniques to make the headline concise, effective, and eye-catching to the reader. 40 English headlines and their Indonesian translations have been selected for the analysis which is performed according to the degrees of equivalence: optimum translation, partial equivalence, zero equivalence. Partial equivalence is divided into two narrower subtypes which are: near-optimum and weak translation. The results show that over some translation procedures have been implemented in rendering headlines.  &nbsp

Linguistic Interventions and Transformative Communicative Disruption

What words we use, and what meanings they have, is important. We shouldn't use slurs; we should use 'rape' to include spousal rape (for centuries we didn’t); we should have a word which picks out the sexual harassment suffered by people in the workplace and elsewhere (for centuries we didn’t). Sometimes we need to change the word-meaning pairs in circulation, either by getting rid of the pair completely (slurs), changing the meaning (as we did with 'rape'), or adding brand new word-meaning pairs (as with 'sexual harassment'). A problem, though, is how to do this. One might worry that any attempt to change language in this way will lead to widespread miscommunication and confusion. I argue that this is indeed so, but that's a feature, not a bug of attempting to change word-meaning pairs. The miscommunications and confusion such changes cause can lead us, via a process I call transformative communicative disruption, to reflect on our language and its use, and this can be further, rather than hinder, our goal of improving language