Search results

This study aims to analyze a backchannel account on news of the coronavirus at the beginning of the pandemic, with information not disseminated in official media due to the social alarm it might cause and the negative image of government management. Specifically, it examines acceptance and dissemination of this type of content in a period of lack of information, while reflecting on what would constitute proper management of this type of channel.

First, based on a literature review, this study classifies possible explanatory variables of online content dissemination into content richness and psychological content. Second, this study performs sentiment analysis of the Twitter backchannel account @COVID_19NEWS and use Qualitative Comparative Analysis to find causal configurations of variables that obtained a high rate of retweets.

The results reveal predominance of one combination of three factors in backchannel information diffusion: emotional, identifying and video content. Other interesting combinations of factors were shown to be attractive enough to contribute to success of the tweets.

Knowledge of the main configurations that attract information dissemination in backchannel accounts is useful for public management of a health crisis such as the Covid-19 outbreak. Rather than suppressing these channels, the authors discuss different solutions.

This study advances scholarship on backchannel communications in emergency situations, providing insights to understand and manage such channels.

Este estudio analiza una cuenta extraoficial sobre noticias del coronavirus al inicio de la pandemia, con información no difundida en los medios oficiales por su posible repercusión en la alarma social y la imagen negativa de la gestión gubernamental. Concretamente examina la aceptación y difusión de este contenido en un periodo de desinformación, así como reflexiona sobre la gestión de este tipo de canales.

En primer lugar, en base a la revisión de la literatura, clasificamos las variables explicativas según la riqueza de contenido y el contenido psicológico. En segundo lugar, sobre la cuenta extraoficial de @COVID_19NEWS en Twitter, realizamos análisis de sentimiento y utilizamos Análisis Comparativo Cualitativo (QCA) para encontrar configuraciones causales de variables que obtuvieron una alta tasa de retweets.

Los resultados revelan la importancia de una combinación de tres factores en la difusión de información del canal secundario: contenido emocional, identificativo y video. Otras combinaciones de factores también contribuyeron al éxito del tweet.

Estas configuraciones podrían ser útiles para la gestión pública ante una crisis sanitaria como la Covid-19, prestando atención a los factores cuya configuración atrae la difusión de información en las RRSS. En lugar de suprimir estos canales, se presentan soluciones para garantizar una colaboración eficaz.

Este estudio realiza una contribución académica a las comunicaciones extraoficiales en situaciones de emergencia, proporcionando información para comprender y gestionar este tipo de canales.

Covid-19, Coronavirus, Canal extraoficial, Twitter, Análisis cualitativo comparado

Trabajo de investigación

在新冠疫情初期, 由于可能引起社会恐慌和政府管理部门的负面形象, 官方媒体缺少相关的新闻报道。本文研究了在这种官方信息匮乏的危机时期, 非正式渠道（backchannel）对于新冠病毒内容的接受和传播情况, 本文同时反思了如何对这类非正式渠道进行正确的管理。

基于文献综述, 我们先将在线内容传播的可能解释变量分为内容丰富度和心理内容这两个方面。其次, 我们对推特上的非正式渠道账户@COVID_19NEWS发布的内容进行情感分析, 并使用定性比较分析法来寻找内容获得高转发率的原因。

结果显示, 对于非正式渠道信息的成功传播, 情绪化、具有辩认度和包含视频内容这三个要素的组合占主导地位。此外, 其他要素的组合也有来助于推文的成功传播和扩散。

了解非正式渠道吸引信息传播的主要原因, 将有利于应对健康危机（例如Covid-19爆发）和进行公共管理。文本讨论了不同的解决方案, 而不是简单地压制这些非正式渠道。

这项研究推进了危机背景下非正式渠道传播的学术研究, 为理解和管理这类非正式渠道提供了见解。

关键词 - Covid-19, 新冠病毒, 非正式渠道, 推特, 定性比较分析

The economic and administrative conditions of countries normatively have an effect on the economy and level of market development. Moreover, it is of great importance for a healthy economy whether the public institutions and organizations are transparent and functioning in accordance with their purpose. The aim of this study is to show whether there is a relationship between transparency and market efficiency.

Correlation analysis has been conducted between prediction accuracy rates, which are obtained by seven different machine learning algorithms and Corruption Perception Index (CPI) levels.

It has been statistically shown that the indices of countries with low corruption levels are harder to predict, which, in turn, can be interpreted as having higher weak-form market efficiency. According to that, an intermediate negative correlation has been found between CPI scores and predictability levels of stock indices. Considering the findings, it can be interpreted that the markets of countries with relatively more transparent and well-functioning public sector have more weak-form market efficiency.

The study can be extended with cutting-edge machine learning and deep learning techniques in future studies. There are very few studies which try to explain factors related to market efficiency. Thus, the authors claim that there is still room for further research in order to determine the factors related to market efficiency, implying that current literature is still far from explaining the causation behind the inefficiencies.

According to findings, the markets of countries with relatively more transparent and well-functioning public sector have more weak-form market efficiency. Based on these findings, in practice, it can be said that more successful predictions can be made using machine learning algorithms in countries with relatively lower CPI scores.

In literature, the factors related to market efficiency are still far from explaining the causation behind the inefficiencies. Thus, it has been investigated whether transparent and well-functioning public institutions and organizations have any relation with market efficiency.

This study aims to focus on creating sales capability as part of new product development (NPD). The aim is to define generic requirements for building sales capability as a part of NPD and to propose a necessary process by defining key activities for sales readiness.

An inductive and qualitative research method was used to construct a sales capability creation process based on a current state analysis in seven companies.

The results indicate that the status of companies’ sales-related planning varies during the NPD, and the related activities are not systematically managed. Considering sales early is necessary to enable a smooth and cost-efficient start of sales, and to avoid unnecessary delays and problems in other functions. At the same time, the companies recognise the need for improvement.

This paper presents a potential process including systematic activities for creating sales capability in conjunction with product development, which is novel to the literature. The proposed process is applicable in aligning industrial company needs.

The era of crowd network is coming and the research of its steady-state is of great importance. This paper aims to establish a crowd network simulation platform and maintaining the relative stability of multi-source dissemination systems.

With this simulation platform, this paper studies the characteristics of “emergence,” monitors the state of the system and according to the fixed point judges the system of steady-state conditions, then uses three control conditions and control methods to control the system status to acquire general rules for maintain the stability of multi-source information dissemination systems.

This paper establishes a novel steady-state maintenance simulation framework. It will be useful for achieving controllability to the evolution of information dissemination and simulating the effectiveness of control conditions for multi-source information dissemination systems.

This paper will help researchers to solve problems of public opinion control in multi-source information dissemination in crowd network.

With the rapid development of internet technology, open online social networks provide a broader platform for information spreading. While dissemination of information provides convenience for life, it also brings many problems such as security risks and public opinion orientation. Various negative, malicious and false information spread across regions, which seriously affect social harmony and national security. Therefore, this paper aims to minimize negative information such as online rumors that has attracted extensive attention. The most existing algorithms for blocking rumors have prevented the spread of rumors to some extent, but these algorithms are designed based on entire social networks, mainly focusing on the microstructure of the network, i.e. the pairwise relationship or similarity between nodes. The blocking effect of these algorithms may be unsatisfactory in some networks because of the sparse data in the microstructure.

An algorithm for minimizing the influence of dynamic rumor based on community structure is proposed in this paper. The algorithm first divides the network into communities, and integrates the influence of each node within communities and rumor influence probability to measure the influence of each node in the entire network, and then selects key nodes and bridge nodes in communities as blocked nodes. After that, a dynamic blocking strategy is adopted to improve the blocking effect of rumors.

Community structure is one of the most prominent features of networks. It reveals the organizational structure and functional components of a network from a mesoscopic level. The utilization of community structure can provide effective and rich information to solve the problem of data sparsity in the microstructure, thus effectively improve the blocking effect. Extensive experiments on two real-world data sets have validated that the proposed algorithm has superior performance than the baseline algorithms.

As an important research direction of social network analysis, rumor minimization has a profound effect on the harmony and stability of society and the development of social media. However, because the rumor spread has the characteristics of multiple propagation paths, fast propagation speed, wide propagation area and time-varying, it is a huge challenge to improve the effectiveness of the rumor blocking algorithm.

The pandemic has enhanced the global phenomenon of disinformation. This paper aims to study the false news concerning COVID-19, spread through social media in Spain, by using the LatamChequea database for a duration from 01/22/2020, when the first false information has been detected, up to 03/09/2021.

A quantitative analysis has been conducted with regard to the correlation between fake news stories and the pandemic state, the motive to share them, their dissemination in other countries and the effectiveness of fact checking. This study is complemented by a qualitative method: a focus group conducted with representatives of different groups within the society.

Fake news has been primarily disseminated through several social networks at the same time, with two peaks taking place in over a half of the said false stories. The first took place from March to April of 2020 during complete lockdown, and we were informed of prevention measures, the country’s situation and the origin of the virus, whereas the second was related to news revolving around the coming vaccines, which occurred between October and November. The audience tends to neither cross-check the information received nor report fake news to competent authorities, and fact-checking methods fail to stop their spread. Further awareness and digital literacy campaigns are thus required in addition to more involvement from governments and technological platforms.

The main limitation of the research is the fact that it was only possible to conduct a focus group of five individuals who do not belong to generation Z due to the restrictions imposed by the pandemic, although a clear contribution to the analysis of the impact of fake news on social networks during the COVID-19 pandemic in Spain can be seen from the privileged experiences in each of the fields of work that were identified. In this sense, the results of the study are not generalizable to a larger population. On the other hand, and with a view to future research, it would be advisable to carry out a more specific study of how fake news affects generation Z.

This research is original in nature, and the findings of this study are valuable for business practitioners and scholars, brand marketers, social media platform owners, opinion leaders and policymakers.

This paper aims to introduce vehicular network platform, routing and broadcasting methods and vehicular positioning enhancement technology, which are three aspects of the applications of intelligent computing in vehicular networks. From this paper, the role of intelligent algorithm in the field of transportation and the vehicular networks can be understood.

In this paper, the authors introduce three different methods in three layers of vehicle networking, which are data cleaning based on machine learning, routing algorithm based on epidemic model and cooperative localization algorithm based on the connect vehicles.

In Section 2, a novel classification-based framework is proposed to efficiently assess the data quality and screen out the abnormal vehicles in database. In Section 3, the authors can find when traffic conditions varied from free flow to congestion, the number of message copies increased dramatically and the reachability also improved. The error of vehicle positioning is reduced by 35.39% based on the CV-IMM-EKF in Section 4. Finally, it can be concluded that the intelligent computing in the vehicle network system is effective, and it will improve the development of the car networking system.

This paper reviews the research of intelligent algorithms in three related areas of vehicle networking. In the field of vehicle networking, these research results are conducive to promoting data processing and algorithm optimization, and it may lay the foundation for the new methods.

This study explores how Lean was deployed in several hospitals in the Apulia region in Italy over 3.5 years.

An exploratory qualitative design was drawn up based on semi-structured interviews.

The drivers of Lean in hospitals were to increase patient satisfaction and improve workplace well-being by eliminating non-value-add waste. The participants highlighted three key elements of the pivotal implementation stages of Lean: introduction, spontaneous and informal dissemination and strategic level implementation and highlighted critical success and failure factors that emerged for each of these stages. During the introduction, training and coaching from an external consultant were among the most impactful factors in the success of pilot projects, while time constraints and the adoption of process analysis tools were the main barriers to implementation. The experiences of the Lean teams strongly influence the process of spontaneous dissemination aided by the celebration of project results and the commitment of the departmental hospital heads.

Lean culture can spread to allow many projects be conducted spontaneously, but the Lean paradigm can struggle to be adopted strategically. Lean in healthcare can fail because of the lack of alignment of Lean with leadership in healthcare and with their strategic vision, a lack of employees' project management skills and crucially the absence of a Lean steering committee.

The absence of managerial expertise and a will to support Lean implementation do not allow for systemic adoption of Lean. This is one of the first and largest long-term case studies on a Lean cross-regional multi-hospital application in healthcare.

This research aims to investigate the impact of the use of social media on the organizational form and function in selected local governments of Indonesia, Thailand and the Philippines.

This research used quantitative and qualitative methods. The researchers not only conducted comparative– explanatory studies among the three ASEAN cities but also used multiple-informant and secondary data analyses. All variables are operationalized into indicators and transformed into a questionnaire in three languages: English, Indonesian and Thai. Primary data for the research were collected using a cross-sectional survey conducted in Bandung City, Indonesia; Iligan City, the Philippines; and Pukhet City, Thailand.

This research found that social media use has not yet affected the internal organizational processes in the three cities. Also, social media use is not appropriated as a space for citizen–government interaction. It is used for only information dissemination to the public; social media seems to have been used for only collecting information from citizens but not for involving them in the decision-making process.

This research covers only three cities in the ASEAN countries, and the findings cannot be generalized to others. Moreover, this research looks at the supply-side dimension or government organization side only. However, the findings confirm that findings of previous research studies that social media use in the local government is only for information dissemination.

Legal bases for social media use could be an urgent matter to address to advance more fundamental changes in government processes.

There is no prior comparative study on the use of social media by local governments in the ASEAN countries. Social media owing to its sense of personalization or sense of community improves communication between citizens and government better than e-government sites; however, as articulated by Mirchandani et al. (2008), social media may hinder rather than facilitate the delivery of services (Mirchandani et al., 2008). This is due to the absence of a legal basis of its use, as well as agreements on the manner of its use, which prevents full integration of social media into the governance process, particularly in the cases of the cities of Iligan, the Philippines, and Phuket, Thailand.

The purpose of this paper is to provide library professionals with insights into students’ fake news judgment and the importance of teaching media and information literacy, not as an option but as a core educational requirement.

Qualtrics was used to collect the study data. Students completed a set of tasks designed in the form of a survey that entailed verifying whether news, stories, images and news sources were real, fake, dubious or trustworthy. Statistical tests were used to asses whether their responses depended on criteria, such as faculty and gender.

No significant relationship exists between the students’ responses and variables, such as gender, student category, fact-checking and source of information. The findings reveal that students’ ability to identify the authoritativeness of information is dependent on the faculty in which they are enrolled.

This paper reports the first known attempt in Lebanon to measure students’ ability in distinguishing fake from real news. The results of this paper can be used by library professionals, particularly in Lebanon, to convey the importance of teaching and embedding media and information literacy into their curriculum.