المؤلفون: Bask, Mikael, 1967, Forsberg, Lars, Östling, Andreas

المصدر: Quarterly Review of Economics and Finance. 94:303-311

مصطلحات موضوعية: Asset pricing, Factor models, Fama-French, News articles, Sentiment

الوصف: Based on 35,344 news articles published in the Financial Times that cover 40 companies that have been included in the Dow Jones Industrial Average, we find that a negative media sentiment in the form of a negative language tone in news articles is a priced factor in five of nine asset-pricing models that aim to explain the cross-section of stock returns. In particular, the sentiment factor is a priced factor in the market model augmented with the sentiment factor in all three samples-the 2005-09 subsample, the 2010-18 subsample, and the 2005-18 full sample-and in the Fama-French three- and five-factor models augmented with the sentiment factor in the 2010-18 subsample. In addition, factor-spanning regressions with the Fama-French five-factor model as the right-hand-side model confirm that the sentiment factor contributes to the model's explanation of the stocks' mean excess returns in the 2005-09 subsample and the 2005-18 full sample.

وصف الملف: electronic

الوصول الحر: https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-530447Test
https://doi.org/10.1016/j.qref.2024.02.008Test
https://uu.diva-portal.org/smash/get/diva2:1865851/FULLTEXT01.pdfTest

المؤلفون: Siripen Pongpaichet, Boonyapat Sukosit, Chitchaya Duangtanawat, Jiramed Jamjongdamrongkit, Chancheep Mahacharoensuk, Kantapong Matangkarat, Pattadon Singhajan, Thanapon Noraset, Suppawong Tuarob

المصدر: IEEE Access, Vol 12, Pp 22778-22802 (2024)

مصطلحات موضوعية: Crime monitoring, online news articles, spatiotemporal information, crime metadata extraction, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

الوصف: Crimes result in not only loss to individuals but also hinder national economic growth. While crime rates have been reported to decrease in developed countries, underdeveloped and developing nations still suffer from prevalent crimes, especially those undergoing rapid expansion of urbanization. The ability to monitor and assess trends of different types of crimes at both regional and national levels could assist local police and national-level policymakers in proactively devising means to prevent and address the root causes of criminal incidents. Furthermore, such a system could prove useful to individuals seeking to evaluate criminal activity for purposes of travel, investment, and relocation decisions. Recent literature has opted to utilize online news articles as a reliable and timely source for information on crime activity. However, most of the crime monitoring systems fueled by such news sources merely classified crimes into different types and visualized individual crimes on the map using extracted geolocations, lacking crucial information for stakeholders to make relevant, informed decisions. To better serve the unique needs of the target user groups, this paper proposes a novel comprehensive crime visualization system that mines relevant information from large-scale online news articles. The system features automatic crime-type classification and metadata extraction from news articles. The crime classification and metadata schemes are designed to serve the need for information from law enforcement and policymakers, as well as general users. Novel interactive spatiotemporal designs are integrated into the system with the ability to assess the severity and intensity of crimes in each region through the novel Criminometer index. The system is designed to be generalized for implementation in different countries with diverse prevalent crime types and languages composing the news articles, owing to the use of deep learning cross-lingual language models. The experiment results reveal that the proposed system yielded 86%, 51%, and 67% F1 in crime type classification, metadata extraction, and closed-form metadata extraction tasks, respectively. Additionally, the results of the system usability tests indicated a notable level of contentment among the target user groups. The findings not only offer insights into the possible applications of interactive spatiotemporal crime visualization tools for proactive policymaking and predictive policing but also serve as a foundation for future research that utilizes online news articles for intelligent monitoring of real-world phenomena.

وصف الملف: electronic resource

العلاقة: https://ieeexplore.ieee.org/document/10424974Test/; https://doaj.org/toc/2169-3536Test

الوصول الحر: https://doaj.org/article/003f2f3b415b41209791d9522f688ce3Test

المؤلفون: Cesar Macias, Hiram Calvo, Omar Juárez Gambino

المصدر: Data in Brief, Vol 53, Iss , Pp 110220- (2024)

مصطلحات موضوعية: News controversy, News articles, X data, Readers perspective, Computer applications to medicine. Medical informatics, R858-859.7, Science (General), Q1-390

الوصف: This paper presents a corpus of Spanish news posts obtained from X with the annotation of controversy made via crowdsourcing. A total of 60 tweets were obtained from 8 different newspapers. For the annotation task, a survey was developed and sent to 31 different participants to answer it with the controversy level they perceived from the news post summary and headline presented on the post. The most frequent selected option was assigned as the initial controversy level of the post. The final annotation of the corpus was made via an analysis of the raw data by computing the Inter Annotator Agreement (IAA). The analysis showed that the binarization of the data was the most convenient way to annotate it. A potential use for this dataset is detailed in further sections.

وصف الملف: electronic resource

العلاقة: http://www.sciencedirect.com/science/article/pii/S2352340924001914Test; https://doaj.org/toc/2352-3409Test

الوصول الحر: https://doaj.org/article/92f6ba1063c2402fb1e34e07f960e3c3Test

المؤلفون: Ortega, Jose, Lawson, Brendan

المصدر: Journalism; Aug2023, Vol. 24 Issue 8, p1657-1678, 22p

مصطلحات موضوعية: JOURNALISM, JOURNALISTS, MORTALITY, COPYRIGHT of news articles

مصطلحات جغرافية: COLOMBIA

مستخلص: This paper explores the relationship between memory, journalism and numbers. It does so through a case study that examines how the Colombian news media reported on a particular figure during a peace negotiation: the 220,000 people who died because of the armed conflict in Colombia. The number was produced by the National Centre for Historical Memory in 2013 in a comprehensive report about the ravages of the Colombian conflict (1958–2012). Following a mix-method approach – a quantitative content analysis and a thematic analysis of the news articles – we find that the way in which journalists reported on the figure contradicts two key aspects of the report. While the report rejects an 'official memory' of the conflict for one that is more open to political and social debate, one characterised less by 'closed truths', the news reports treated the number as a fact and very rarely provided a form of contestation to it. Moreover, while the report emphasises the need for clarification over distortion and concealment when constructing memory, the news articles misrepresented those accountable for the casualties: Fuerzas Armadas Revolucionarias de Colombia (FARC) was consistently positioned as the main illegal armed organisation responsible for the death toll. This representation ran counter to the findings from the report that emphasised the way paramilitary groups, rather than guerrilla groups (e.g. FARC), were more responsible for the killings. Considering our findings, we argue that an adherence to accuracy by journalists is more desirable than a practice of vagueness in the contribution to memory formation in post-conflict contexts. [ABSTRACT FROM AUTHOR]

: Copyright of Journalism is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

المؤلفون: Ernesto Cordero Collo, Jr.

المصدر: Informasi, Vol 53, Iss 1, Pp 39-54 (2023)

مصطلحات موضوعية: science news articles, framing, news media functions, politicization, Communication. Mass media, P87-96

الوصف: This century has necessitated scholars to probe the credence of science in the news reportage of the Covid-19 pandemic. Therefore, this paper aims to establish the locus of science as treated by CNN against the backdrop of this global health crisis. Using Nisbet’s (2009) typology as the new paradigm in public engagement as informed by content analysis, this paper argues that CNN Philippines’ news articles are mostly framed as scientific/technical uncertainty which holds science with the highest esteem in decision-making, but it also disregards its authority for political reasons. As guided by Yanovitzky and Weber (2019), this paper also articulates that the functions of CNN as a news media organization in the reportage of science are mobilization and awareness which provoke action among policy actors through relevant information. Further, this paper offers a perceptive look into an emerging dimension for science communication scholars: the gulf between science and politics which surfaces the politicization of key pandemic decisions.

وصف الملف: electronic resource

العلاقة: https://journal.uny.ac.id/index.php/informasi/article/view/56692Test; https://doaj.org/toc/0126-0650Test; https://doaj.org/toc/2502-3837Test

الوصول الحر: https://doaj.org/article/cb5043c3386247bab767e8b54a764124Test

المؤلفون: Yuan, Yue, Liu, Kan, Wang, Yanli

المصدر: Aslib Journal of Information Management, 2022, Vol. 75, Issue 2, pp. 407-429.

الوصول الحر: http://www.emeraldinsight.com/doi/10.1108/AJIM-05-2022-0264Test

المؤلفون: Ángel Díaz-Pacheco, Rafael Guerrero-Rodríguez, Miguel Á. Álvarez-Carmona, Ansel Y. Rodríguez-González, Ramón Aranda

المصدر: Journal of King Saud University: Computer and Information Sciences, Vol 35, Iss 9, Pp 101746- (2023)

مصطلحات موضوعية: Destination image, Online news articles, Deep learning, Topic modeling, Mexico, Electronic computers. Computer science, QA75.5-76.95

الوصف: Automatic discovery of underlying themes in a document collection is a valuable task across many disciplines. Advanced techniques can be challenging for non-experts in data science to understand. To address these challenges, this work proposes a comprehensive deep-learning-based method for gathering, preprocessing, analyzing, and classifying text data to discover topics in extensive collections of documents. This method produces results understandable to humans, which is especially valuable in fields outside of data science. We tested the proposed method on a corpus of all news articles (in English) from the USA and Canada about Cancun, a popular tourist destination in Mexico, published between July 2021 and July 2022. Despite negative media coverage, we discovered a positive attitude toward Cancun’s amenities. This information can help destination management organizations monitor the destination’s digital reputation and design effective communication campaigns for potential visitors who consult these sources of information.

وصف الملف: electronic resource

العلاقة: http://www.sciencedirect.com/science/article/pii/S1319157823003002Test; https://doaj.org/toc/1319-1578Test

الوصول الحر: https://doaj.org/article/3cf147df1aab4fd8a4fe4871b574c5d5Test

المؤلفون: Mohammed Altamimi, Abdulaziz M. Alayba

المصدر: Data in Brief, Vol 50, Iss , Pp 109460- (2023)

مصطلحات موضوعية: Arabic news articles, Data analysis, Classification, Natural language processing (NLP), Computer applications to medicine. Medical informatics, R858-859.7, Science (General), Q1-390

الوصف: In this paper, we present a modern standard Arabic dataset based on Arabic news articles collected over a one-year period from 01/01/2021 to 12/31/2021. In total, from 12 Arabic news websites, over 500,000 articles were collected, the selection of which was driven by a variety of topics, including sports, economies, local news, politics, tech, tourism, entertainment, cars, health, and art. The development of this dataset will enable data scientists to explore and experiment effectively in the field of natural language processing, and the dataset can also be used to develop machine learning and deep learning models to classify articles according to topic. The dataset is available for download athttps://github.com/alaybaa/ArabicArticlesDataset/tree/main.

وصف الملف: electronic resource

العلاقة: http://www.sciencedirect.com/science/article/pii/S2352340923005607Test; https://doaj.org/toc/2352-3409Test

الوصول الحر: https://doaj.org/article/ab153bffb8964010a788149ca0dec8f0Test

المؤلفون: Sidra Abbas, Shtwai Alsubai, Gabriel Avelino Sampedro, Mideth Abisado, Ahmad S. Almadhor, Natalia Kryvinska, Monji Mohamed Zaidi

المصدر: IEEE Access, Vol 11, Pp 98415-98426 (2023)

مصطلحات موضوعية: Active learning, authorship identification, text analysis, machine learning, news articles, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

الوصف: Over time, the amount of textual data has increased drastically, especially due to the publication of articles. As a consequence, there has been a rise in anonymous content. Research is being conducted to determine alternative methods for identifying unknown text authors. To this end, a system has to be developed to accurately determine the author of unknown texts, given a group of writing samples. Active Learning is utilized in this study because it iteratively selects the most informative samples to include in the training set, which enables a more precise and accurate authorship identification approach with fewer examples. Makes it useful for analyzing the rising amount of anonymous content and identifying unknown text authors. This study proposes a novel approach that utilizes active learning (AL) based machine models, namely Logistic Regression (AL-LR), Random Forest (AL-RF), XGboost (AL-XGB), and Multilayer Perceptron (AL-MLP) for authorship identification. The proposed approach extracts valuable characteristics of the writer using the Term Frequency-Inverse Document Frequency (TF-IDF). This study’s selected comprehensive dataset, “All the news,” is divided into three subsets: Article 1, Article 2, and Article 3. We have restricted the dataset’s scope and selected the top 50 authors for our experimentation. The experimental outcomes reveal that the proposed AL-XGB model achieves superior performance on Article 1 of the “All the news” dataset. Further, the AL-LR model performed well on Article 2, and the AL-MLP performed well on Article 3. The results suggest using the proposed approach for authorship identification.

وصف الملف: electronic resource

العلاقة: https://ieeexplore.ieee.org/document/10235957Test/; https://doaj.org/toc/2169-3536Test

الوصول الحر: https://doaj.org/article/64418a814e554efba98675461e32a4fbTest

المؤلفون: Gabbioneta, Claudia¹ (AUTHOR) claudia.gabbioneta@newcastle.ac.uk, De Carlo, Manuela² (AUTHOR) manuela.decarlo@iulm.it

المصدر: International Journal of Tourism Research. May2019, Vol. 21 Issue 3, p291-301. 11p.

مصطلحات موضوعية: *TOURISM marketing, DESTINATION image (Tourism), COPYRIGHT of news articles, TOURIST attractions, IMAGE processing

مستخلص: Despite the relevance of news articles as autonomous image formation agents, we still have limited understanding of their influence on destination image and the conditions under which such influence occurs. This paper analyses the role of news articles and two moderating conditions—prior destination experience and news involvement—in destination image formation. It shows that the number of news articles individuals read is positively associated with their image of the destination, that news involvement enhances the influence of the news articles on destination image formation, and that this influence holds even after controlling for prior destination experience. [ABSTRACT FROM AUTHOR]

: Copyright of International Journal of Tourism Research is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)