Automated text analysis methods have made possible the classification of large corpora of text by measures such as topic and tone. Here, we provide a guide to help researchers navigate the ...consequential decisions they need to make before any measure can be produced from the text. We consider, both theoretically and empirically, the effects of such choices using as a running example efforts to measure the tone of New York Times coverage of the economy. We show that two reasonable approaches to corpus selection yield radically different corpora and we advocate for the use of keyword searches rather than predefined subject categories provided by news archives. We demonstrate the benefits of coding using article segments instead of sentences as units of analysis. We show that, given a fixed number of codings, it is better to increase the number of unique documents coded rather than the number of coders for each document. Finally, we find that supervised machine learning algorithms outperform dictionaries on a number of criteria. Overall, we intend this guide to serve as a reminder to analysts that thoughtfulness and human validation are key to text-as-data methods, particularly in an age when it is all too easy to computationally classify texts without attending to the methodological choices therein.
The main German-speaking countries (Germany, Austria, and Switzerland) have implemented digital contact tracing apps to assist the authorities with COVID-19 containment strategies. Low user rates for ...these apps can affect contact tracing and, thus, its usefulness in controlling the spread of the novel coronavirus.
This study aimed to assess the early perceptions of people living in the German-speaking countries and compare them with the frames portrayed in the newspapers during the first wave of the COVID-19 pandemic.
We conducted qualitative interviews with 159 participants of the SolPan project. Of those, 110 participants discussed contact tracing apps and were included in this study. We analyzed articles regarding contact tracing apps from 12 newspapers in the German-speaking countries.
Study participants perceived and newspaper coverage in all German-speaking countries framed contact tracing apps as governmental surveillance tools and embedded them in a broader context of technological surveillance. Participants identified trust in authorities, respect of individual privacy, voluntariness, and temporary use of contact tracing apps as prerequisites for democratic compatibility. Newspapers commonly referenced the use of such apps in Asian countries, emphasizing the differences in privacy regulation among these countries.
The uptake of digital contact tracing apps in German-speaking countries may be undermined due to privacy risks that are not compensated by potential benefits and are rooted in a deeper skepticism towards digital tools. When authorities plan to implement new digital tools and practices in the future, they should be very transparent and proactive in communicating their objectives and the role of the technology-and how it differs from other, possibly similar, tools. It is also important to publicly address ethical, legal, and social issues related to such technologies prior to their launch.
Qualitative content analysis as a kind of systematic analysis of qualitative data in which the latent values and meanings of the text are tried to be identified, described, and interpreted, is one of ...the most widely used qualitative methods in urban planning research and urban studies. However, the excessive flexibility and development of the method in other theoretical fields have obscured how to use it in the field of planning and urban studies. In this paper, we have tried to propose a procedural model that is suitable for the specific conditions and issues of the field by analyzing the content of the documents obtained from the systematic review of the theoretical literature of planning and urban studies that have used this method. This procedural model explains the process of qualitative content analysis within five stages: choosing the type and theoretical context of data, explaining the objectives, deciding on how to analyze the data, deciding on how to interpret the data, and application of the interpretation results. Proposing the procedural model of qualitative content analysis that comes from the field of planning and urban studies can help, in addition to disambiguating the function of the method, make the method more visible and more correctly used in the field.
Abstract
Meta-theoretical focus is given to how communication researchers are approaching and hypothesizing moderation. A moderation typology is offered and an evaluation of the field’s common ...practices for positing moderation reveals an inability to discern between three overarching classifications (Contributory, Contingent, Cleaved). A content analysis of eight communication journals reveals moderation hypotheses lacking a level of precision that can best aid the field’s knowledge generation. In addition, vague hypothesizing is leaving communication researchers vulnerable to the commitment of Type III error (i.e., correctly rejecting a null hypothesis for the wrong reason). Recommendations are provided in an effort to improve the field’s conceptualization and presentation of moderation.
With the rapid development of video distribution and broadcasting, affective video content analysis has attracted a lot of research and development activities recently. Predicting emotional responses ...of movie audiences is a challenging task in affective computing, since the induced emotions can be considered relatively subjective. In this article, we propose a multimodal local-global attention network (MMLGAN) for affective video content analysis. Inspired by the multimodal integration effect, we extend the attention mechanism to multi-level fusion and design a multimodal fusion unit to obtain a global representation of affective video. The multimodal fusion unit selects key parts from multimodal local streams in the local attention stage and captures the information distribution across time in the global attention stage. Experiments on the LIRIS-ACCEDE dataset, the MediaEval 2015 and 2016 datasets, the FilmStim dataset, the DEAP dataset and the VideoEmotion dataset demonstrate the effectiveness of our approach when compared with the state-of-the-art methods.
•There is a growing interest in applying blockchain technology in supply chain operations.•Research on blockchain configuration receives less attention as compared to others, such as impact and ...function.•Discussion on sustainability is limited as compared to other themes.•More research should be carried out under the themes of coordination, performance and order management.•The voices of different stakeholders should be considered in academic research.
In the past few years, blockchain, the underlying technology of Bitcoin, has received considerable attention from academia and industry. It is widely accepted that blockchain technology causes disruptive changes in supply chain operations that can overcome supply chain difficulties encountered in realizing information sharing, maintaining traceability in the entire process and improving operational efficiency. However, the application of blockchain technology in the supply chain field is still in its infancy, which limits an understanding of its potential. This article uses descriptive and content analysis to review publications related to blockchain-based supply chains between 2017 and 2020 inclusive. To fully explore research on blockchain-based supply chains, four well-designed questions are proposed and addressed, namely, the value of blockchain in supply chains, the attraction of scholars to particular supply chain themes, the development of research methodologies and illustration types in adopting blockchain in supply chains, and the types of industries involved in blockchain-based supply chains. The results reveal that there is growing interest in applying blockchain technology to supply chain operations. A detailed analysis of findings is provided to identify the future opportunities of blockchain-based supply chains, including prospects for tertiary industries and concerted efforts that are necessary to explore sustainability themes. This article provides valuable information to help scholars and practitioners better determine the relevant research topics to accelerate the development of blockchain-based supply chains.
E-petitions have become a popular vehicle for political activism, but studying them has been difficult because efficient methods for analyzing their content are currently lacking. Researchers have ...used topic modeling for content analysis, but current practices carry some serious limitations. While modeling may be more efficient than manually reading each petition, it generally relies on unsupervised machine learning and so requires a dependable training and validation process. And so this paper describes a framework to train and validate Latent Dirichlet Allocation (LDA), the simplest and most popular topic modeling algorithm, using e-petition data. With rigorous training and evaluation, 87% of LDA-generated topics made sense to human judges. Topics also aligned well with results from an independent content analysis by the Pew Research Center, and were strongly associated with corresponding social events. Computer-assisted content analysts can benefit from our guidelines to supervise every process of training and evaluation of LDA. Software developers can benefit from learning the demands of social scientists when using LDA for content analysis. These findings have significant implications for developing LDA tools and assuring validity and interpretability of LDA content analysis. In addition, LDA topics can have some advantages over subjects extracted by manual content analysis by reflecting multiple themes expressed in texts, by extracting new themes that are not highlighted by human coders, and by being less prone to human bias.
We investigate the effects of sentiment and issue salience on emotionally labeled responses to posts from political actors on Facebook (i.e., Reactions). We use an automated content analysis of ...Facebook posts and voter survey data in a multilevel negative binomial regression approach. Findings show that the sentiment of a post relates to the number of "Love" and "Angry" Reactions. Furthermore, if a post addresses an issue that constituents perceive as salient, this positively influences the number of "Angry" Reactions only. We also find that the effect of sentiment on "Angry" Reactions is highest when issue salience is low.
Summary
Active interviewing approaches can exploit the verbal differences between truthtellers and liars, thus improving detecting deception. One such method is the Reality Interview (RI) aimed to ...facilitate recall from truthtellers, while increasing the difficulty for liars. This study investigated whether the RI could improve the diagnostic accuracy of the Reality Monitoring and the Criteria‐Based Content Analysis. Liars and truthtellers were either asked to freely recall an event or interviewed with the RI. As hypothesized, the RI improved the discriminability of Reality Monitoring and Criteria‐Based Content Analysis over Free Recall. Honest responses were longer, and the RI increased the word count difference between honest and false statements. However, after correcting for word count, results were no longer significant, showing its importance for deception detection. Nonetheless, the RI increased verbal differences between truthtellers and liars, demonstrating that using the RI with verbal credibility assessment tools is a powerful combination for investigative interviewing.
The influence of TikTok has reached the news media, which has adapted to the logic of the platform, in a context marked by the incidental consumption of news, virality and the intermediation of ...technology in access to information. The popularity of this social network invites news outlets to address a young audience on a platform characterized by visual and short content and dynamics defined by algorithmic recommendations, trending hashtags and challenges. Based on an exploratory search of news media and programmes on TikTok from around the world, we selected 234 accounts and conducted a content analysis of the 19 news media and programmes identified with a verified profile and general thematic scope. The results point to a progressive incorporation of the media since 2019, with the purpose of informing, positioning their brand and adapting to the logic of TikTok in a new approach to journalism for younger generations.
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