scholarly journals Bringing Shape to Textual Data – A Feasible Demonstration

Author(s):  
Anoud Shaikh ◽  
Naeem Ahmed Mahoto ◽  
Mukhtiar Ali Unar

The Internet has revolutionized the communication paradigm. This has led towards immense amount of unstructured data (i.e. textual data), which is a major source to get useful knowledge about people in several application domains. TM (Text Mining) extracts high quality information to discover knowledge by drawing patterns and relationships in textual data. This field has taken great attention of the research community. As a result, several attempts have been made to propose, introduce and refine techniques applied for uncovering knowledge from text data. This study aims at: (1) presenting existing TM techniques in the scientific literature, (2) reporting challenges/issues and gaps that still need attention, and (3) proposing a framework to bring shape to textual data. A prototype has been developed to demonstrate the effectiveness and potential worth of proposed approach to display how unstructured data (i.e. news articles in this study) has been brought to a shape representing interesting knowledge. The proposed framework implements basic NLP (Natural Language Processing) functions in combination of AYLIEN API (Application Programming Interface) functions. The results reveal the fact that how events, celebrities and popular news-items have been covered in the electronic media, and it also represents subjectivity of topical news events. The news coverage trends highlight the significance of daily news events, which may assist in getting insight about the media groups.

Author(s):  
Alba Córdoba-Cabús ◽  
Manuel Hidalgo-Arjona ◽  
Álvaro López-Martín

The aim of this work is to study the news coverage by the main Spanish generalist newspapers on Twitter during the campaign for the Community of Madrid elections in 2021 (n = 2,709). Natural language processing techniques and machine learning algorithms are applied to identify the predominant topic related to the elections and the mentions of candidates and political parties by each media, and to calibrate the emotional value of the messages published by El país, El mundo, Eldiario.es, and El confidencial. Among other findings, the results reveal how the media coverage focused mainly on campaign events and electoral debates. Despite the detection of minor differences between the newspapers, a general pattern emerges through this content, with a notable dominance of Isabel Díaz Ayuso but little influence of Rocío Monasterio as the lead candidates for their party. The sentiment analysis reveals the political alignment of each newspaper, using mainly negative messages with the aim of reducing the importance of a candidate or political party. While El país and Eldiario.es focused their criticism on Vox and the Partido Popular, El mundo and El confidencial criticized the actions of the national government, the PSOE’s proposal to join forces with Unidas Podemos, and Vox’s position, as well as emphasizing the disaster faced by Ciudadanos. It can be deduced that the media contributed to Ayuso’s success and to the consolidation of her image as an individual distinct from her own party. Resumen Se examina la cobertura informativa en las principales cabeceras generalistas españolas en Twitter durante la campaña de las elecciones a la Comunidad de Madrid en 2021 (n=2.709). Mediante técnicas de procesamiento de lenguaje natural y algoritmos de aprendizaje automático se identifica el tema preponderante vinculado a los comicios, se señala la incidencia de los candidatos y los partidos en cada medio y se calibra el valor emocional de los mensajes publicados por El país, El mundo, Eldiario.es y El confidencial. Entre otras pesquisas, los resultados evidencian cómo la cobertura mediática se centra, principalmente, en los actos de campaña y en los debates electorales. Pese a detectar pequeñas disimilitudes entre los diarios, se intuye un patrón generalizado: la notable incidencia de Isabel Díaz Ayuso y la escasa influencia de Rocío Monasterio como cabeza de lista en el contenido. A partir del análisis de sentimientos se constata la alineación partidista de las cabeceras, exponiendo, sobre todo, mensajes en tono negativo con la intención de mermar la relevancia de algún candidato o formación política. Mientras El país y Eldiario.es situaron en el centro de sus críticas a Vox y al Partido Popular, El mundo y El confidencial recriminaron la actuación del gobierno central, menospreciaron la proposición del PSOE a Unidas Podemos en aras de aunar votos, censuraron la postura de Vox e, incluso, insistieron en la debacle de Ciudadanos. Se deduce que los propios medios han contribuido al modelo de éxito de Ayuso y a la consolidación de su figura, propiciando ese individualismo y el distanciamiento de las siglas de su propio partido.


FLOBAMORA ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 44-51
Author(s):  
Yohanes Museng Ola Buluamang

The implementation of the eight NTT Province development agendas (2013-2018) received attention in the daily news of Pos Kupang, Timor Ekspress and Victory News. The purpose of this study included identifying the quantity of news from the three newspapers, knowing the description of the news and testing the hypothesis of the different news coverage of three newspapers. The results of the analysis show that the most dominant news theme reported by Pos Kupang daily (71 news), Timor Ekspress (78 news) and Victory News (125 news) is the agenda of the development of populist economy and tourism. The description of the news by the Pos Kupang daily is dominated by neutral portrayals (109 news), Timor Ekspress is dominated by positive depictions (109 news) and Victory News is dominated by negative depictions (180 news). The results of the analysis show that there are significant differences in the news theme and news depiction of the NTT province's eight development agenda for 2013-2018 between the three newspapers. This confirms the importance of an issue that the media considers in determining the media agenda and the way the media express a reality. Keywords: NTT Province Development Agenda, Newspapers, Media Agenda


2019 ◽  
pp. 30-44
Author(s):  
Elena A. Fedorovau ◽  
Svetlana O. Musienko ◽  
Igor S. Demin ◽  
Fedor Yu. Fedorov ◽  
Dmitriy O. Afanasyev
Keyword(s):  

2021 ◽  
pp. 001041402198975
Author(s):  
Ryan E. Carlin ◽  
Timothy Hellwig ◽  
Gregory J. Love ◽  
Cecilia Martínez-Gallardo ◽  
Matthew M. Singer

Public evaluations of the economy are key for understanding how citizens develop policy opinions and monitor government performance. But what drives economic evaluations? In this article, we argue the context in which information about the economy is distributed shapes economic perceptions. In high-quality information environments—where policies are transparent, the media is free, and political opposition is robust—mass perceptions closely track economic conditions. In contrast, compromised information environments provide openings for political manipulation, leading perceptions to deviate from business cycle fluctuations. We test our argument with unique data from eight Latin American countries. Results show restrictions on access to information distort the public’s view of economic performance. The ability of voters to sanction governments is stronger when democratic institutions and the media protect citizens’ access to independent, unbiased information. Our findings highlight the importance of accurate evaluations of the economy for government accountability and democratic responsiveness.


Author(s):  
Irina Wedel ◽  
Michael Palk ◽  
Stefan Voß

AbstractSocial media enable companies to assess consumers’ opinions, complaints and needs. The systematic and data-driven analysis of social media to generate business value is summarized under the term Social Media Analytics which includes statistical, network-based and language-based approaches. We focus on textual data and investigate which conversation topics arise during the time of a new product introduction on Twitter and how the overall sentiment is during and after the event. The analysis via Natural Language Processing tools is conducted in two languages and four different countries, such that cultural differences in the tonality and customer needs can be identified for the product. Different methods of sentiment analysis and topic modeling are compared to identify the usability in social media and in the respective languages English and German. Furthermore, we illustrate the importance of preprocessing steps when applying these methods and identify relevant product insights.


2021 ◽  
pp. 1063293X2098297
Author(s):  
Ivar Örn Arnarsson ◽  
Otto Frost ◽  
Emil Gustavsson ◽  
Mats Jirstrand ◽  
Johan Malmqvist

Product development companies collect data in form of Engineering Change Requests for logged design issues, tests, and product iterations. These documents are rich in unstructured data (e.g. free text). Previous research affirms that product developers find that current IT systems lack capabilities to accurately retrieve relevant documents with unstructured data. In this research, we demonstrate a method using Natural Language Processing and document clustering algorithms to find structurally or contextually related documents from databases containing Engineering Change Request documents. The aim is to radically decrease the time needed to effectively search for related engineering documents, organize search results, and create labeled clusters from these documents by utilizing Natural Language Processing algorithms. A domain knowledge expert at the case company evaluated the results and confirmed that the algorithms we applied managed to find relevant document clusters given the queries tested.


Proceedings ◽  
2021 ◽  
Vol 77 (1) ◽  
pp. 17
Author(s):  
Andrea Giussani

In the last decade, advances in statistical modeling and computer science have boosted the production of machine-produced contents in different fields: from language to image generation, the quality of the generated outputs is remarkably high, sometimes better than those produced by a human being. Modern technological advances such as OpenAI’s GPT-2 (and recently GPT-3) permit automated systems to dramatically alter reality with synthetic outputs so that humans are not able to distinguish the real copy from its counteracts. An example is given by an article entirely written by GPT-2, but many other examples exist. In the field of computer vision, Nvidia’s Generative Adversarial Network, commonly known as StyleGAN (Karras et al. 2018), has become the de facto reference point for the production of a huge amount of fake human face portraits; additionally, recent algorithms were developed to create both musical scores and mathematical formulas. This presentation aims to stimulate participants on the state-of-the-art results in this field: we will cover both GANs and language modeling with recent applications. The novelty here is that we apply a transformer-based machine learning technique, namely RoBerta (Liu et al. 2019), to the detection of human-produced versus machine-produced text concerning fake news detection. RoBerta is a recent algorithm that is based on the well-known Bidirectional Encoder Representations from Transformers algorithm, known as BERT (Devlin et al. 2018); this is a bi-directional transformer used for natural language processing developed by Google and pre-trained over a huge amount of unlabeled textual data to learn embeddings. We will then use these representations as an input of our classifier to detect real vs. machine-produced text. The application is demonstrated in the presentation.


2016 ◽  
Vol 17 (4) ◽  
pp. 593-615 ◽  
Author(s):  
Isabelle Guinaudeau ◽  
Anna M Palau

This article argues that external factors of EU coverage in the media need to be reassessed against domestic factors, in particular how parties modulate media attention to EU affairs. We explain which parties may set the EU on the media agenda, and how parties interact with events depending on the level of conflict over EU issues. Drawing on the first long-term analysis of partisan agenda-setting of EU affairs in the media – based on ARIMA time-series models of monthly data collected for six newspapers from 1990 to 2015 – we determine the scale of partisan agenda-setting and find partial support for our model. Political parties do not face the intrusion of EU issues, but some of them are actively involved in this process.


2021 ◽  
Vol 2 (2) ◽  
pp. 193-207
Author(s):  
Kathryn Shine ◽  
Shane L. Rogers

This study examines Australian teachers (n = 268) and parents’ (n = 206) self-reported perceptions of education news coverage and how the coverage affects them. Overall, the participants reported a perception that news coverage of teachers, schools, the education system and standardised testing was generally negative in tone. Participants reported typically feeling demoralised by negative stories and inspired by positive stories. A high importance was placed upon the public perception of education by participants. However, trust in the media reporting of educational issues was low. An exception to this general pattern of findings was that participants did not place as much importance upon the public perception of standardised testing and reported being less affected by negative or positive stories on that topic compared to the other education aspects. This research is one of the few studies to investigate the potential emotional impact that news coverage of education can have on media consumers.


Author(s):  
Steven Casey

From Pearl Harbor to Hiroshima and Nagasaki, a group of highly courageous correspondents covered America’s war against Japan. Based on a wealth of previously untapped primary sources, War Beat, Pacific provides the first comprehensive account of what these reporters witnessed, what they were allowed to publish, and how their reports shaped the home front’s perception of some of the most pivotal battles in American history. In a dramatic and fast-paced narrative, the book takes us from MacArthur’s doomed defense on the Philippines and the navy’s overly strict censorship policy at the time of Midway through the bloody battles on Guadalcanal, New Guinea, Tarawa, Saipan, Leyte and Luzon, Iwo Jima and Okinawa, detailing the cooperation, as well as conflict, between the media and the military as they grappled with the enduring problem of limiting a free press during a period of extreme crisis. At the heart of this book are the brave, sometimes tragic stories of reporters like Clark Lee and Vern Haugland of the Associated Press, Byron Darnton and Tillman Durdin of the New York Times, Stanley Johnston and Al Noderer of the Chicago Tribune, George Weller of the Chicago Daily News, Keith Wheeler of the Chicago Times, and Robert Sherrod of Time magazine. Twenty-three correspondents died while reporting on the Pacific War. Many more sustained serious wounds. War Beat, Pacific shows how both the casualties and the survivors deserve to be remembered as America’s golden generation of journalists.


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