Automatic Content Analysis of Media Framing by Text Mining Techniques

Lin, Fu‐ren; Hao, De; Liao, Da-Chi

doi:10.1109/hicss.2016.348

Cited by 10 publications

(3 citation statements)

References 20 publications

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“…As a recently emerged method for scholars to study a variety of phenomena with a minimum amount of human interference ( Lin et al, 2016 ; Yang and Kang, 2018 ; Kang and Yang, 2022 ), this objective data categorization and interpretation approach can address problems that we have found in traditional literature review analysis and meta-analysis studies ( Guzman et al, 2020 ; Song et al, 2021 ). Additionally, a text mining method also offers researchers the excellent opportunity to systematically review and analyze many retrieved articles objectively, without human errors (Lin, cited in Yang and Kang, 2018 ).…”

Section: Methodsmentioning

confidence: 99%

A Literature Analysis of Consumer Privacy Protection in Augmented Reality Applications in Creative and Cultural Industries: A Text Mining Study

Kang

2022

Front. Psychol.

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Digital reality technologies (such as AR, VR, and MR) have recently become a key component of promoting creative and cultural industries (CCIs) worldwide to transform static cultural heritage exhibits into more engaging, entertaining, and immersive experiences. These technologies present an exciting example of studying how consumers would respond to the potential invasion of privacy due to these technologies. This literature review study mainly focuses on one essential branch of CCIs: museums and their applications of digital reality technologies. Because many of these location-based AR applications by museums are inherently sensitive to users’ locational information, there is also a rising concern of the potential infringement of personal privacy (RQ1). A thorough examination of existing literature on how consumers respond to privacy concerns related to the museum’s AR applications will help uncover how scholars have approached and studied these crucial issues in the literature (RQ2). Unlike traditional literature review analyses, we employed a text mining of retrieved 715 studies articles from Business Source Complete and Engineering Village (E.I.) databases to answer our two research questions. Our study found that privacy and user(s) /visitor(s) has dramatically increased since 2017, echoing the rising concerns of other privacy-invasive technologies. Most notably, key phrases extracted from the literature corpus include “security and privacy,” “privacy and security,” “privacy risks,” “privacy concerns,” “privacy issues,” “user privacy,” “location privacy,” “privacy protection,” and “privacy preserving” that are most pertinent to the rapid implementation of AR technology in the museum sector. Discussions and implications are provided.

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Section: Methodsmentioning

confidence: 99%

A Literature Analysis of Consumer Privacy Protection in Augmented Reality Applications in Creative and Cultural Industries: A Text Mining Study

Kang

2022

Front. Psychol.

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“…The tweets were compiled using text-mining techniques, which allow information to be extracted from big data with minimal human interference (Lin et al, 2016). RStudio free software (version 1.4.1103) and VOSON Dash library data were used for data collection.…”

Section: O2mentioning

confidence: 99%

Journalism in Democracy: A Discourse Analysis of Twitter Posts on the Ferrerasgate Scandal

Sanz

Berdón-Prieto

Izquierdo

2023

MaC

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This research analyses the discourse on Twitter surrounding the “Ferrerasgate” scandal involving the Spanish journalist Antonio García Ferreras, director and host of the television show <em>Al Rojo Vivo </em>(La Sexta, Spanish TV channel). It examines the main object of criticism, the tone of the discourse, the argumentation made by users, as well as the existence of hate in their rhetoric. The tweets included in the study’s sample (<em>N </em>= 2,846), posted between 5 and 15 July 2022 and extracted on 16 July 2022, were examined in two complementary phases. The first entailed a quantitative content analysis of the messages and the second analysed whether hate speech was found in the sample as a whole. The Sketch Engine tool was used to determine whether “crypto hate speech” existed in the sample as a whole, and to whom it was targeted. The results reveal that “Ferrerasgate” sparked a debate that spilt over into journalism across the board, calling into question the media’s role in a democracy. The most prominent arguments were the condemnation of misinformation, lack of independence, and absence of professionalism in the journalism sector. It should be noted that most of the messages were destructive in tone; hate was found in the tweets analysed, although these did not represent a high percentage in relation to the total sample.

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“…Another important area of machine learning is deep learning [43,44], natural language processing (NLP) [25], and text mining, which are computer and statistical techniques developed in the early nineties [45] used to discover new non-explicit information in source documents [46,47] and was aimed at discovering patterns through the right combination of artificial intelligence, machine learning, statistics, and data mining [48]. Text mining is currently used for various operations such as in image analysis [49], in biomedical fields (hospitals and clinics) [50,51], in the analysis of profiles of university students [52], in geosciences (geology, geophysics, geochemistry and remote sensing) [53], and in the automotive sector [54], among others.…”

Section: Literature Reviewmentioning

confidence: 99%

Discovery Model Based on Analogies for Teaching Computer Programming

2021

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Teaching the fundamentals of computer programming in a first course (CS1) is a complex activity for the professor and is also a challenge for them. Nowadays, there are several teaching strategies for dealing with a CS1 at the university, one of which is the use of analogies to support the abstraction process that a student needs to carry for the appropriation of fundamental concepts. This article presents the results of applying a discovery model that allowed for the extraction of patterns, linguistic analysis, textual analytics, and linked data when using analogies for teaching the fundamental concepts of programming by professors in a CS1 in university programs that train software developers. For that reason, a discovery model based on machine learning and text mining was proposed using natural language processing techniques for semantic vector space modeling, distributional semantics, and the generation of synthetic data. The discovery process was carried out using nine supervised learning methods, three unsupervised learning methods, and one semi-supervised learning method involving linguistic analysis techniques, text analytics, and linked data. The main findings showed that professors include keywords, which are part of the technical computer terminology, in the form of verbs in the statement of the analogy and combine them in quantitative contexts with neutral or positive phrases, where numerical examples, cooking recipes, and games were the most used categories. Finally, a structure is proposed for the construction of analogies to teach programming concepts and this was validated by the professors and students.

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Automatic Content Analysis of Media Framing by Text Mining Techniques

Cited by 10 publications

References 20 publications

A Literature Analysis of Consumer Privacy Protection in Augmented Reality Applications in Creative and Cultural Industries: A Text Mining Study

A Literature Analysis of Consumer Privacy Protection in Augmented Reality Applications in Creative and Cultural Industries: A Text Mining Study

Journalism in Democracy: A Discourse Analysis of Twitter Posts on the Ferrerasgate Scandal

Discovery Model Based on Analogies for Teaching Computer Programming

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