Noticias em eLiteracias

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✇ Online Information Review

A corpus of debunked and verified user-generated videos

12 de Novembro de 2018, 03:04
Online Information Review, Volume 43, Issue 1, Page 72-88, February 2019.
Purpose As user-generated content (UGC) is entering the news cycle alongside content captured by news professionals, it is important to detect misleading content as early as possible and avoid disseminating it. The purpose of this paper is to present an annotated dataset of 380 user-generated videos (UGVs), 200 debunked and 180 verified, along with 5,195 near-duplicate reposted versions of them, and a set of automatic verification experiments aimed to serve as a baseline for future comparisons. Design/methodology/approach The dataset was formed using a systematic process combining text search and near-duplicate video retrieval, followed by manual annotation using a set of journalism-inspired guidelines. Following the formation of the dataset, the automatic verification step was carried out using machine learning over a set of well-established features. Findings Analysis of the dataset shows distinctive patterns in the spread of verified vs debunked videos, and the application of state-of-the-art machine learning models shows that the dataset poses a particularly challenging problem to automatic methods. Research limitations/implications Practical limitations constrained the current collection to three platforms: YouTube, Facebook and Twitter. Furthermore, there exists a wealth of information that can be drawn from the dataset analysis, which goes beyond the constraints of a single paper. Extension to other platforms and further analysis will be the object of subsequent research. Practical implications The dataset analysis indicates directions for future automatic video verification algorithms, and the dataset itself provides a challenging benchmark. Social implications Having a carefully collected and labelled dataset of debunked and verified videos is an important resource both for developing effective disinformation-countering tools and for supporting media literacy activities. Originality/value Besides its importance as a unique benchmark for research in automatic verification, the analysis also allows a glimpse into the dissemination patterns of UGC, and possible telltale differences between fake and real content.
✇ Online Information Review

Context-aware restricted Boltzmann machine meets collaborative filtering

12 de Novembro de 2018, 03:01
Online Information Review, Ahead of Print.
Purpose The purpose of this paper is to propose an approach to incorporate contextual information into collaborative filtering (CF) based on the restricted Boltzmann machine (RBM) and deep belief networks (DBNs). Traditionally, neither the RBM nor its derivative model has been applied to modeling contextual information. In this work, the authors analyze the RBM and explore how to utilize a user’s occupation information to enhance recommendation accuracy. Design/methodology/approach The proposed approach is based on the RBM. The authors employ user occupation information as a context to design a context-aware RBM and stack the context-aware RBM to construct DBNs for recommendations. Findings The experiments on the MovieLens data sets show that the user occupation-aware RBM outperforms other CF models, and combinations of different context-aware models by mutual information can obtain better accuracy. Moreover, the context-aware DBNs model is superior to baseline methods, indicating that deep networks have more qualifications for extracting preference features. Originality/value To improve recommendation accuracy through modeling contextual information, the authors propose context-aware CF approaches based on the RBM. Additionally, the authors attempt to introduce hybrid weights based on information entropy to combine context-aware models. Furthermore, the authors stack the RBM to construct a context-aware multilayer network model. The results of the experiments not only convey that the context-aware RBM has potential in terms of contextual information but also demonstrate that the combination method, the hybrid recommendation and the multilayer neural network extension have significant benefits for the recommendation quality.
✇ Online Information Review

An exploratory approach to the computational quantification of journalistic values

12 de Novembro de 2018, 02:57
Online Information Review, Volume 43, Issue 1, Page 133-148, February 2019.
Purpose News algorithms not only help the authors to efficiently navigate the sea of available information, but also frame information in ways that influence public discourse and citizenship. Indeed, the likelihood that readers will be exposed to and read given news articles is structured into news algorithms. Thus, ensuring that news algorithms uphold journalistic values is crucial. In this regard, the purpose of this paper is to quantify journalistic values to make them readable by algorithms through taking an exploratory approach to a question that has not been previously investigated. Design/methodology/approach The author matched the textual indices (extracted from natural language processing/automated content analysis) with human conceptions of journalistic values (derived from survey analysis) by implementing partial least squares path modeling. Findings The results suggest that the numbers of words or quotes news articles contain have a strong association with the survey respondent assessments of their balance, diversity, importance and factuality. Linguistic polarization was an inverse indicator of respondents’ perception of balance, diversity and importance. While linguistic intensity was useful for gauging respondents’ perception of sensationalism, it was an ineffective indicator of importance and factuality. The numbers of adverbs and adjectives were useful for estimating respondents’ perceptions of factuality and sensationalism. In addition, the greater numbers of quotes, pair quotes and exclamation/question marks in news headlines were associated with respondents’ perception of lower journalistic values. The author also found that the assessment of journalistic values influences the perception of news credibility. Research limitations/implications This study has implications for computational journalism, credibility research and news algorithm development. Originality/value It represents the first attempt to quantify human conceptions of journalistic values with textual indices.
✇ Online Information Review

Location impact on source and linguistic features for information credibility of social media

12 de Novembro de 2018, 02:54
Online Information Review, Volume 43, Issue 1, Page 89-112, February 2019.
Purpose Social media platforms provide a source of information about events. However, this information may not be credible, and the distance between an information source and the event may impact on that credibility. Therefore, the purpose of this paper is to address an understanding of the relationship between sources, physical distance from that event and the impact on credibility in social media. Design/methodology/approach In this paper, the authors focus on the impact of location on the distribution of content sources (informativeness and source) for different events, and identify the semantic features of the sources and the content of different credibility levels. Findings The study found that source location impacts on the number of sources across different events. Location also impacts on the proportion of semantic features in social media content. Research limitations/implications This study illustrated the influence of location on credibility in social media. The study provided an overview of the relationship between content types including semantic features, the source and event locations. However, the authors will include the findings of this study to build the credibility model in the future research. Practical implications The results of this study provide a new understanding of reasons behind the overestimation problem in current credibility models when applied to different domains: such models need to be trained on data from the same place of event, as that can make the model more stable. Originality/value This study investigates several events – including crisis, politics and entertainment – with steady methodology. This gives new insights about the distribution of sources, credibility and other information types within and outside the country of an event. Also, this study used the power of location to find alternative approaches to assess credibility in social media.
✇ Online Information Review

Event news detection and citizens community structure for disaster management in social networks

8 de Novembro de 2018, 10:25
Online Information Review, Volume 43, Issue 1, Page 113-132, February 2019.
Purpose Nowadays, the event detection is so important in gathering news from social media. Indeed, it is widely employed by journalists to generate early alerts of reported stories. In order to incorporate available data on social media into a news story, journalists must manually process, compile and verify the news content within a very short time span. Despite its utility and importance, this process is time-consuming and labor-intensive for media organizations. Because of the afore-mentioned reason and as social media provides an essential source of data used as a support for professional journalists, the purpose of this paper is to propose the citizen clustering technique which allows the community of journalists and media professionals to document news during crises. Design/methodology/approach The authors develop, in this study, an approach for natural hazard events news detection and danger citizen’ groups clustering based on three major steps. In the first stage, the authors present a pipeline of several natural language processing tasks: event trigger detection, applied to recuperate potential event triggers; named entity recognition, used for the detection and recognition of event participants related to the extracted event triggers; and, ultimately, a dependency analysis between all the extracted data. Analyzing the ambiguity and the vagueness of similarity of news plays a key role in event detection. This issue was ignored in traditional event detection techniques. To this end, in the second step of our approach, the authors apply fuzzy sets techniques on these extracted events to enhance the clustering quality and remove the vagueness of the extracted information. Then, the defined degree of citizens’ danger is injected as input to the introduced citizens clustering method in order to detect citizens’ communities with close disaster degrees. Findings Empirical results indicate that homogeneous and compact citizen’ clusters can be detected using the suggested event detection method. It can also be observed that event news can be analyzed efficiently using the fuzzy theory. In addition, the proposed visualization process plays a crucial role in data journalism, as it is used to analyze event news, as well as in the final presentation of detected danger citizens’ clusters. Originality/value The introduced citizens clustering method is profitable for journalists and editors to better judge the veracity of social media content, navigate the overwhelming, identify eyewitnesses and contextualize the event. The empirical analysis results illustrate the efficiency of the developed method for both real and artificial networks.
✇ Online Information Review

Are mega-journals a publication outlet for lower quality research? A bibliometric analysis of Spanish authors in PLOS ONE

5 de Novembro de 2018, 08:49
Online Information Review, Ahead of Print.
Purpose Open-access mega-journals (OAMJs), which apply a peer-review policy based solely on scientific soundness, elicit opposing views. Sceptical authors believe that OAMJs are simply an easy target to publish uninteresting papers that would not be accepted in more selective traditional journals. The purpose of this paper is to investigate any differences in scholars’ considerations of OAMJs by analysing the productivity and impact of Spanish authors in Biology and Medicine who publish in PLOS ONE. Design/methodology/approach Scopus was used to identify the most prolific Spanish authors in Biology and Medicine between 2013 and 2017 and to determine their publication patterns in PLOS ONE. Any differences in terms of citation impact between Spanish authors who publish frequently in PLOS ONE and the global Spanish output in Biology and Medicine were measured. Findings Results show a moderate correlation between the total number of articles published by prolific authors in Biology and Medicine and the number of articles they publish in PLOS ONE. Authors who publish frequently in PLOS ONE tend to publish more frequently than average in Quartile 1 and Top 10 per cent impact journals and their articles are more frequently cited than average too, suggesting that they do not submit to PLOS ONE for the purpose of gaining easier publication in a high-impact journal. Research limitations/implications The study is limited to one country, one OAMJ and one discipline and does not investigate whether authors select PLOS ONE for what they might regard as their lower quality research. Originality/value Very few studies have empirically addressed the implications of the soundness-based peer-review policy applied by OAMJs.
✇ Online Information Review

Social media analytics: analysis and visualisation of news diffusion using NodeXL

24 de Outubro de 2018, 07:30
Online Information Review, Volume 43, Issue 1, Page 149-160, February 2019.
Purpose The purpose of this paper is to provide an overview of NodeXL in the context of news diffusion. Journalists often include a social media dimension in their stories but lack the tools to get digital photos of the virtual crowds about which they write. NodeXL is an easy to use tool for collecting, analysing, visualising and reporting on the patterns found in collections of connections in streams of social media. With a network map patterns emerge that highlight key people, groups, divisions and bridges, themes and related resources. Design/methodology/approach This study conducts a literature review of previous empirical work which has utilised NodeXL and highlights the potential of NodeXL to provide network insights of virtual crowds during emerging news events. It then develops a number of guidelines which can be utilised by news media teams to measure and map information diffusion during emerging news events. Findings One emergent software application known as NodeXL has allowed journalists to take “group photos” of the connections among a group of users on social media. It was found that a diverse range of disciplines utilise NodeXL in academic research. Furthermore, based on the features of NodeXL, a number of guidelines were developed which provide insight into how to measure and map emerging news events on Twitter. Social implications With a set of social media network images a journalist can cover a set of social media content streams and quickly grasp “situational awareness” of the shape of the crowd. Since social media popular support is often cited but not documented, NodeXL social media network maps can help journalists quickly document the social landscape utilising an innovative approach. Originality/value This is the first empirical study to review literature on NodeXL, and to provide insight into the value of network visualisations and analytics for the news media domain. Moreover, it is the first empirical study to develop guidelines that will act as a valuable resource for newsrooms looking to acquire insight into emerging news events from the stream of social media posts. In the era of fake news and automated accounts, i.e., bots the ability to highlight opinion leaders and ascertain their allegiances will be of importance in today’s news climate.
✇ Online Information Review

Phones, privacy, and predictions

24 de Outubro de 2018, 07:26
Online Information Review, Ahead of Print.
Purpose Mobile phones have become one of the most favored devices to maintain social connections as well as logging digital information about personal lives. The privacy of the metadata being generated in this process has been a topic of intense debate over the last few years, but most of the debate has been focused on stonewalling such data. At the same time, such metadata is already being used to automatically infer a user’s preferences for commercial products, media, or political agencies. The purpose of this paper is to understand the predictive power of phone usage features on individual privacy attitudes. Design/methodology/approach The present study uses a mixed-method approach, involving analysis of mobile phone metadata, self-reported survey on privacy attitudes and semi-structured interviews. This paper analyzes the interconnections between user’s social and behavioral data as obtained via their phone with their self-reported privacy attitudes and interprets them based on the semi-structured interviews. Findings The findings from the study suggest that an analysis of mobile phone metadata reveals vital clues to a person’s privacy attitudes. This study finds that multiple phone signals have significant predictive power on an individual’s privacy attitudes. The results motivate a newer direction of automatically inferring a user’s privacy attitudes by leveraging their phone usage information. Practical implications An ability to automatically infer a user’s privacy attitudes could allow users to utilize their own phone metadata to get automatic recommendations for privacy settings appropriate for them. This study offers information scientists, government agencies and mobile app developers, an understanding of user privacy needs, helping them create apps that take these traits into account. Originality/value The primary value of this paper lies in providing a better understanding of the predictive power of phone usage features on individual privacy attitudes.
✇ Online Information Review

Profile reliability to improve recommendation in social-learning context

18 de Outubro de 2018, 01:33
Online Information Review, Ahead of Print.
Purpose Generally, the user requires customized information reflecting his/her current needs and interests that are stored in his/her profile. There are many sources which may provide beneficial information to enrich the user’s interests such as his/her social network for recommendation purposes. The proposed approach rests basically on predicting the reliability of the users’ profiles which may contain conflictual interests. The paper aims to discuss this issue. Design/methodology/approach This approach handles conflicts by detecting the reliability of neighbors’ profiles of a user. The authors consider that these profiles are dependent on one another as they may contain interests that are enriched from non-reliable profiles. The dependency relationship is determined between profiles, each of which contains interests that are structured based on k-means algorithm. This structure takes into consideration not only the evolutionary aspect of interests but also their semantic relationships. Findings The proposed approach was validated in a social-learning context as evaluations were conducted on learners who are members of Moodle e-learning system and Delicious social network. The quality of the created interest structure is assessed. Then, the result of the profile reliability is evaluated. The obtained results are satisfactory. These results could promote recommendation systems as the selection of interests that are considered of enrichment depends on the reliability of the profiles where they are stored. Research limitations/implications Some specific limitations are recorded. As the quality of the created interest structure would evolve in order to improve the profile reliability result. In addition, as Delicious is used as a main data source for the learner’s interest enrichment, it was necessary to obtain interests from other sources, such as e-recruitement systems. Originality/value This research is among the pioneer papers to combine the semantic as well as the hierarchical structure of interests and conflict resolution based on a profile reliability approach.
✇ Online Information Review

Researchers’ online visibility: tensions of visibility, trust and reputation

15 de Outubro de 2018, 07:17
Online Information Review, Volume 43, Issue 3, Page 426-439, June 2019.
Purpose The purpose of this paper is to understand what role researchers assign to online representations on the new digital communication sites that have emerged, such as Academia, ResearchGate or Mendeley. How are researchers’ online presentations created, managed, accessed and, more generally, viewed by academic researchers themselves? And how are expectations of the academic reward system navigated and re-shaped in response to the possibilities afforded by social media and other digital tools? Design/methodology/approach Focus groups have been used for empirical investigation to learn about the role online representation is assigned by the concerned researchers. Findings The study shows that traditional scholarly communication documents are what also scaffolds trust and builds reputation in the new setting. In this sense, the new social network sites reinforce rather than challenge the importance of formal publications. Originality/value An understanding of the different ways in which researchers fathom the complex connection between reputation and trust in relation to online visibility as a measure of, or at least an attempt at, publicity (either within academia or outside it) is essential. This paper emphasizes the need to tell different stories by exploring how researchers understand their own practices and reasons for them.
✇ Online Information Review

A bibliometric analysis of event detection in social media

15 de Outubro de 2018, 07:13
Online Information Review, Volume 43, Issue 1, Page 29-52, February 2019.
Purpose The purpose of this paper is to explore the research status and development trend of the field of event detection in social media (ED in SM) through a bibliometric analysis of academic publications. Design/methodology/approach First, publication distributions are analyzed including the trends of publications and citations, subject distribution, predominant journals, affiliations, authors, etc. Second, an indicator of collaboration degree is used to measure scientific connective relations from different perspectives. A network analysis method is then applied to reveal scientific collaboration relations. Furthermore, based on keyword co-occurrence analysis, major research themes and their evolutions throughout time span are discovered. Finally, a network analysis method is applied to visualize the analysis results. Findings The area of ED in SM has received increasing attention and interest in academia with Computer Science and Engineering as two major research subjects. The USA and China contribute the most to the area development. Affiliations and authors tend to collaborate more with those within the same country. Among the 14 identified research themes, newly emerged themes such as Pharmacovigilance event detection are discovered. Originality/value This study is the first to comprehensively illustrate the research status of ED in SM by conducting a bibliometric analysis. Up-to-date findings are reported, which can help relevant researchers understand the research trend, seek scientific collaborators and optimize research topic choices.
✇ Online Information Review

Extended model of online privacy concern: what drives consumers’ decisions?

11 de Outubro de 2018, 09:39
Online Information Review, Ahead of Print.
Purpose The purpose of this paper is to investigate the relationship between individual and societal determinants of online privacy concern (OPC) and behavioral intention of internet users. The study also aims to assess the degree of reciprocity between consumers’ perceived benefits of using the internet and their OPC in the context of their decision-making process in the online environment. Design/methodology/approach The study proposes comprehensive model for analysis of antecedents and consequences of OPC. Empirical analysis is performed using the PLS–SEM approach on a representative sample of 2,060 internet users. Findings The findings show that computer anxiety and perceived quality of regulatory framework are significant antecedents of OPC, while traditional values and inclinations toward security, family and social order; and social trust are not. Furthermore, the study reveals that perceived benefits of using the internet are the predominant factor explaining the intention to share personal information and adopt new technologies, while OPC dominates in explanation of protective behavior. Research limitations/implications Although the authors tested an extended model, there might be other individual characteristics driving the level of OPC. This research covers just one country and further replications should be conducted to confirm findings in diverse socio-economic contexts. It is impossible to capture the real behavior with survey data, and experimental studies may be needed to verify the research model. Practical implications Managers should work toward maximizing perceived benefits of consumers’ online interaction with the company, while at the same time being transparent about the gathered data and their intended purpose. Considering the latter, companies should clearly communicate their compliance with the emerging new data protection regulation. Originality/value New extended model is developed and empirically tested, consolidating current different streams of research into one conceptual model.
✇ Online Information Review

What the fake? Assessing the extent of networked political spamming and bots in the propagation of #fakenews on Twitter

11 de Outubro de 2018, 09:37
Online Information Review, Volume 43, Issue 1, Page 53-71, February 2019.
Purpose The purpose of this paper is to examine one of the largest data sets on the hashtag use of #fakenews that comprises over 14m tweets sent by more than 2.4m users. Design/methodology/approach Tweets referencing the hashtag (#fakenews) were collected for a period of over one year from January 3 to May 7 of 2018. Bot detection tools were employed, and the most retweeted posts, most mentions and most hashtags as well as the top 50 most active users in terms of the frequency of their tweets were analyzed. Findings The majority of the top 50 Twitter users are more likely to be automated bots, while certain users’ posts like that are sent by President Donald Trump dominate the most retweeted posts that always associate mainstream media with fake news. The most used words and hashtags show that major news organizations are frequently referenced with a focus on CNN that is often mentioned in negative ways. Research limitations/implications The research study is limited to the examination of Twitter data, while ethnographic methods like interviews or surveys are further needed to complement these findings. Though the data reported here do not prove direct effects, the implications of the research provide a vital framework for assessing and diagnosing the networked spammers and main actors that have been pivotal in shaping discourses around fake news on social media. These discourses, which are sometimes assisted by bots, can create a potential influence on audiences and their trust in mainstream media and understanding of what fake news is. Originality/value This paper offers results on one of the first empirical research studies on the propagation of fake news discourse on social media by shedding light on the most active Twitter users who discuss and mention the term “#fakenews” in connection to other news organizations, parties and related figures.
✇ Online Information Review

Subject analysis of LIS data archived in a Figshare using co-occurrence analysis

2 de Outubro de 2018, 02:49
Online Information Review, Volume 43, Issue 2, Page 256-264, April 2019.
Purpose Based on the data from Figshare repositories, the purpose of this paper is to analyze which research data are actively produced and shared in the interdisciplinary field of library and information science (LIS). Design/methodology/approach Co-occurrence analysis was performed on keywords assigned to research data in the field of LIS, which were archived in the Figshare repository. By analyzing the keyword network using the pathfinder algorithm, the study identifies key areas where data production is actively conducted in LIS, and examines how these results differ from the conventional intellectual structure of LIS based on co-citation or bibliographic coupling analysis. Findings Four major domains – Open Access, Scholarly Communication, Data Science and Informatics – and 15 sub-domains were created. The keywords with the highest global influence appeared as follows, in descending order: “open access,” “scholarly communication” and “altmetrics.” Originality/value This is the first study to understand the key areas that actively produce and utilize data in the LIS field.
✇ Online Information Review

“Warning! You’re entering a sick zone”

19 de Setembro de 2018, 12:38
Online Information Review, Ahead of Print.
Purpose Traditional public health methods for tracking contagious diseases are increasingly complemented with digital tools, which use data mining, analytics and crowdsourcing to predict disease outbreaks. In recent years, alongside these public health tools, commercial mobile apps such as Sickweather have also been released. Sickweather collects information from across the web, as well as self-reports from users, so that people can see who is sick in their neighborhood. The purpose of this paper is to examine the privacy and surveillance implications of digital disease tracking tools. Design/methodology/approach The author performed a content and platform analysis of two apps, Sickweather and HealthMap, by using them for three months, taking regular screenshots and keeping a detailed user journal. This analysis was guided by the walkthrough method and a cultural-historical activity theory framework, taking note of imagery and other content, but also the app functionalities, including characteristics of membership, “rules” and parameters of community mobilization and engagement, monetization and moderation. This allowed me to study HealthMap and Sickweather as modes of governance that allow for (and depend upon) certain actions and particular activity systems. Findings Draw on concepts of network power, the surveillance assemblage, and Deleuze’s control societies, as well as the data gathered from the content and platform analysis, the author argues that disease tracking apps construct disease threat as omnipresent and urgent, compelling users to submit personal information – including sensitive health data – with little oversight or regulation. Originality/value Disease tracking mobile apps are growing in popularity yet have received little attention, particularly regarding privacy concerns or the construction of disease risk.
✇ Online Information Review

Toward a maturity model for the application of social media in healthcare

18 de Setembro de 2018, 06:45
Online Information Review, Volume 43, Issue 3, Page 404-425, June 2019.
Purpose The advent of new technologies and change of patients’ behavioral patterns have triggered the provision of medical services through social media. Although the intersection between social media and health has received considerable research attention, there is little research on how health institutions implement social media strategy; thus a roadmap is required to navigate these technological initiatives. So, the purpose of this paper is to overcome this challenge by developing the Health 2.0 maturity model in the healthcare field. Design/methodology/approach To obtain this aim, the mixed method was applied in this research. In the first step, qualitative research method was used. In this step, along with comprehensive literature review, semi-structured interviews were conducted with the healthcare professionals to find the practices and capabilities of Health 2.0. In the second step, the proposed key dimensions (KD) were assessed and prioritized based on the views of the healthcare professionals using the quantitative survey method. Finally, by considering the architecture of Health 2.0 maturity model, the KDs were assigned to maturity levels based on their priority of implementation using a focus group. Findings The proposed maturity model is composed of six KDs and five maturity levels based on the Capability Maturity Model Integration architecture. The KDs, as well as their implementation order and weights in the proposed maturity model are presented as a roadmap for applying Health 2.0 effectively. Practical implications Employing the Health 2.0 maturity model enables health institutions to assess the current social media capabilities and guide them to select appropriate strategies for progress. Due to the descriptive nature of the proposed model, it allows managers to conduct process-based assessments regarding health 2.0 implementation. Originality/value Health 2.0 has been a recurring theme on the agenda of healthcare institutions, but no sensitive tool is available to measure its growth processes. This paper explores the much ignored but critically important subject of Health 2.0 maturity model and its implementation roadmap. The main contribution of this paper is to introduce an integrated roadmap containing the most important capabilities of Health 2.0. The proposed model is both descriptive and prescriptive in nature, and has a significant theoretical contribution to healthcare studies. This paper provides a mechanism to benchmark Health 2.0 efforts and to develop a progressive strategy that would improve its activities.
✇ Online Information Review

Chinese online public opinions on the Two-Child Policy

18 de Setembro de 2018, 06:37
Online Information Review, Volume 43, Issue 3, Page 387-403, June 2019.
Purpose The purpose of this paper is to use Weibo as a window to examine the Chinese netizens’ online attitudes and responses to two sets of population policy: the Selective Two-Child Policy (Phase 2) and the Universal Two-Child Policy. The population policy change from the rigid One-Child Policy to the Selective Two-Child Policy then to the Universal Two-Child Policy aroused great attention of the Chinese people. Design/methodology/approach This research uses the crawler technique to extract data on the Sina Weibo platform. Through opinion mining of Weibo posts on two sets of population policy, the Weibo users’ online opinions on the Two-Child Policy are analyzed from two perspectives: their attention intensity and sentiment tendency. The research also use the State Bureau of Statistics of China’s national population data between 2011 and 2016 to examine the Chinese people’s actual birth behaviors after implementing the two different sets of the Two-Child Policy. Findings The research findings indicate that the Selective Two-Child Policy (Phase 2) and the Universal Two-Child Policy are good examples of thematic public sphere of Weibo. Weibo posts on the two sets of the Two-Child Policy have undergone different opinion cycles. People from economically developed regions and populous regions have paid more attention to both sets of Two-Child Policy than their counterparts in the less developed and less populated regions. Men pay more attention to the Two-Child Policy than women do. Despite people’s huge attention to the new population policy, the population growth after the policy is not sustainable. Research limitations/implications The new population policy alone is difficult to boost China’s population within a short period of time. The Chinese Government must provide its people with enough incentives and supporting welfare to make the population growth happen. Originality/value These findings have important implications for understanding the dynamics of online opinion formation and changing population policy in China.
✇ Online Information Review

Sexual health information-seeking behavior on a social media site: predictors of best answer selection

13 de Setembro de 2018, 09:18
Online Information Review, Volume 42, Issue 6, Page 880-897, October 2018.
Purpose The purpose of this paper is to identify sexual health information needs and the cognitive and affective factors correlated with the best answer chosen by social Q&A users. Design/methodology/approach The study collected questions and answers regarding sexual health information on a social Q&A site, and analyzed the questions and a paired sample composed of best and non-best answers (n=480). Findings The main information needs of consumers are human development, sexual behavior, and sexual health. Best answers are more likely to include both cognitive (higher level of readability, risky information, social norms) and affective factors (empathy, positive/negative feelings, and optimistic information) than non-best answers. Research limitations/implications The study illuminates the roles of social Q&A as a unique platform to discuss sensitive health topics due to the fact that consumers use such social media sites as critical complementary health information sources. Practical implications If health information providers develop information with the factors that the study suggests, not only will it be more adopted by consumers, but it will also ameliorate the quality concerns about online health information. Originality/value Previous studies only investigated the most prevalent factors, rather than the most effective ones, which have a greater influence on best answer selection. This study compares the best answers and the non-best answers to overcome the limitations of the previous studies. Above all, the study applied the persuasion concepts to address the cognitive and affective perspectives to the answer evaluations of social Q&A.
✇ Online Information Review

Predicting the success of Twitter in healthcare

13 de Setembro de 2018, 09:18
Online Information Review, Volume 42, Issue 6, Page 898-922, October 2018.
Purpose The purpose of this paper is to predict Twitter satisfaction by healthcare professionals through integrating constructs of Csikszentmihalyi’s flow theory, quality dimensions and usefulness. Design/methodology/approach Survey responses of 108 physicians from a variety of specialisations in the United Arab Emirates have been validated and analysed by means of partial least squares-based structural equation modelling method using smartPLS software. Findings Service quality has emerged as the most influential quality dimension that positively impact flow state and perceived usefulness of Twitter, while information quality, surprisingly, does not show any effect. The findings also indicate that flow state plays a significant role in shaping physicians’ satisfaction with Twitter. The study also enhances our understanding concerning the effects of perceived usefulness on flow state and satisfaction. Research limitations/implications Understanding factors that influence Twitter satisfaction can help healthcare managers construct appropriate intervention strategies for maximising professional benefits of social media and minimising user resistance. This is important because top managers usually ratify traditional practices that are only of limited effect. Also, the findings help vendors to accentuate user’s concerns in addition to system functionalities in social media applications. Originality/value The paper is an early attempt to propose a model for social media success in a professional context in general and healthcare in particular. It also one of first studies that examine social media satisfaction through integrating contemporary information system success and acceptance models with flow theory.
✇ Online Information Review

Image search and retrieval problems in web search engines

13 de Setembro de 2018, 09:17
Online Information Review, Volume 42, Issue 6, Page 752-767, October 2018.
Purpose The purpose of this paper is to investigate image search and retrieval problems in selected search engines in relation to Persian writing style challenges. Design/methodology/approach This study is an applied one, and to answer the questions the authors used an evaluative research method. The aim of the research is to explore the morphological and semantic problems of Persian language in connection with image search and retrieval among the three major and widespread search engines: Google, Yahoo and Bing. In order to collect the data, a checklist designed by the researcher was used and then the data were analyzed by descriptive and inferential statistics. Findings The results indicate that Google, Yahoo and Bing search engines do not pay enough attention to morphological and semantic features of Persian language in image search and retrieval. This research reveals that six groups of Persian language features include derived words, derived/compound words, Persian and Arabic Plural words, use of dotted T and the use of spoken language and polysemy, which are the major problems in this area. In addition, the results suggest that Google is the best search engine of all in terms of compatibility with Persian language features. Originality/value This study investigated some new aspects of the above-mentioned subject through combining morphological and semantic aspects of Persian language with image search and retrieval. Therefore, this study is an interdisciplinary research, the results of which would help both to offer some solutions and to carry out similar research on this subject area. This study will also fill a gap in research studies conducted so far in this area in Farsi language, especially in image search and retrieval. Moreover, findings of this study can help to bridge the gap between the user’s questions and search engines (systems) retrievals. In addition, the methodology of this paper provides a framework for further research on image search and retrieval in databases and search engines.
✇ Online Information Review

Protecting privacy on the web

13 de Setembro de 2018, 09:17
Online Information Review, Volume 42, Issue 6, Page 734-751, October 2018.
Purpose The purpose of this paper is to examine the extent to which HTTPS encryption and Google Analytics services have been implemented on academic library websites, and discuss the privacy implications of free services that introduce web tracking of users. Design/methodology/approach The home pages of 279 academic libraries were analyzed for the presence of HTTPS, Google Analytics services and privacy-protection features. Findings Results indicate that HTTPS implementation on library websites is not widespread, and many libraries continue to offer non-secured connections without an automatically enforced redirect to a secure connection. Furthermore, a large majority of library websites included in the study have implemented Google Analytics and/or Google Tag Manager, yet only very few connect securely to Google via HTTPS or have implemented Google Analytics IP anonymization. Practical implications Librarians are encouraged to increase awareness of this issue and take concerted and coherent action across five interrelated areas: implementing secure web protocols (HTTPS), user education, privacy policies, informed consent and risk/benefit analyses. Originality/value Third-party tracking of users is prevalent across the web, and yet few studies demonstrate its extent and consequences for academic library websites.
✇ Online Information Review

What drives internet users’ willingness to provide personal information?

13 de Setembro de 2018, 09:17
Online Information Review, Volume 42, Issue 6, Page 923-939, October 2018.
Purpose Considering that users’ information privacy concerns may affect the development of e-commerce, the purpose of this paper is to explore what drives internet users’ willingness to provide personal information; further, the paper examines how extrinsic rewards moderate the relationship between users’ information privacy concerns and willingness to provide personal information. Design/methodology/approach Data collected from 345 valid internet users in the context of electronic commerce were analyzed using the partial least squares approach. Findings The result showed that agreeableness, risk-taking propensity and experience of privacy invasion were three main antecedents of information privacy concerns among the seven individual factors. Additionally, information privacy concerns did not significantly affect users’ willingness to provide personal information in the privacy calculation mechanism; however, extrinsic rewards directly affected users’ disclosure intention. The authors found that extrinsic rewards had not moderated the relationship between users’ information privacy concerns and their willingness to provide personal information. Originality/value This study is an exploratory effort to develop and validate a model for explaining why internet users were willing to provide personal information. The results of this study are helpful to researchers in developing theories of information privacy concerns and to practitioners in promoting internet users’ willingness to provide personal information in an e-commerce context.
✇ Online Information Review

Mediating impact of fan-page engagement on social media connectedness and followers purchase intention

7 de Setembro de 2018, 08:32
Online Information Review, Volume 42, Issue 7, Page 1082-1105, November 2018.
Purpose The purpose of this paper is to identify the mediating effect of fan-page followers’ engagement activities and moderating role of followers’ demographic profile and trust level on their purchase intention. Design/methodology/approach This study utilised the customer engagement behaviour and consumer involvement theory as a foundation to explore the impact of variables. Structural equation modelling was utilised to test the model with the data collected from 307 Facebook fan pages’ followers of five Malaysian companies. Findings It was shown that following fan pages will influence fan page engagement, which in turn affects purchase intention and social media connectedness. Further analysis indicated that the impact of “follow” and “engagement” on purchase intention differs between genders, ages, level of trust and income. Research limitations/implications The study serves as a basic fundamental guideline for academics and researchers to interpret the concept of following fan pages and engagement actions and its effects on purchase intention and social media connectivity, as well as opening a vast area of unexplored researches on the subject of social media. Practical implications The research provides information for business-to-consumer companies in utilising fan page based on user categories. Originality/value This study proposes the application of an empirically tested framework to the fan-page follow actions. The authors argue that this framework can provide a useful foundation for future social commerce research. The results would help academics be aware of fan page and its user’s engagement actions, which will provide a new avenue of research.
✇ Online Information Review

Building digital state

6 de Setembro de 2018, 12:31
Online Information Review, Volume 43, Issue 2, Page 301-323, April 2019.
Purpose The purpose of this paper is to review and illustrate historical milestones and evolutionary stages of public sector reforms in such a typical transitional society as Kazakhstan through the prism of existing e-government development strategies, implementation models and institutional regulations. Design/methodology/approach The research is mostly based on a retrospective analysis of technology-driven public sector reforms and content analysis of various e-government strategies and platforms implemented by national and local executive authorities in Kazakhstan for the last two decades. Findings The results of the analysis has confirmed previously made assumptions that typical developing states tend to adopt different non-linear and multidimensional implementation strategies in advancing e-government reforms in comparison with developed countries. As it turns out, the continuity of actual stages or levels of such development not always corresponds in a consecutive manner to the formal phases of the most popular e-government maturity models proposed previously in academic literature. Research limitations/implications One of the fundamental limitations of the case study is that its findings and recommendations could relate only to a limited number of countries that have similar political, socioeconomic and administrative contexts. Taking into account the fact that Kazakhstan is not only a typical developing economy but also a transitional post-communist and post-totalitarian society that has its own unique political and socioeconomic features of governance, the results of case study could not be generalized and extrapolated to all developing countries, presumably narrowing them only to a very limited number of similar states, mostly, in Eastern Europe, Caucasus and Central Asia. Practical implications The main practical contribution of the article is that it provides a close review of e-government politics in Kazakhstan that could be helpful for policy makers and practitioners in evaluating, learning and improving the work of various technology-driven public sector projects in the area, especially from a regulatory point of view. Originality/value This inherently ethnographic narrative, which is based on the analysis of e-government legislation and implementation strategies derived from diverse administrative practices, could be interesting for those who seek to understand an ever-changing truly evolutionary nature of technology-driven public sector reforms in a typical transitional society.
✇ Online Information Review

The asymmetric effect of review valence on numerical rating

6 de Setembro de 2018, 12:29
Online Information Review, Volume 43, Issue 2, Page 283-300, April 2019.
Purpose The basic assumption is that there is a symmetric relationship between review valence and rating, but what if review valence and rating were linked asymmetrically? There are few studies which have investigated the situations in which positive and negative online reviews exert different influences on ratings. This study considers brand strength as having an important moderating role because the average rating of existing reviews for a particular product is a heuristic cue for decision makers. Thus, the purpose of this paper is to argue that an asymmetric relationship between review content valence and numerical rating will depend on brand strength. Design/methodology/approach The authors have conducted a sentiment analysis via text mining, using self-developed computer programs to retrieve a data set from the TripAdvisor website. Findings This study finds there is an asymmetric relationship between review valence (verbal) and numerical rating. The authors further find brand strength to have an important moderating role. For a stronger brand, negative review content will have a greater impact on numerical ratings than positive review content, while for a weaker brand, positive review content will have a greater impact on numerical ratings than negative review content. Practical implications Marketers could adopt sentiment analysis via text mining of online reviews as a valid measure or predictor of consumer satisfaction or numerical ratings. Strong brands should direct more attention to negative reviews, because in such reviews the negative impact transcends the positive. In contrast, weak brands should aim to exploit as many positive reviews as possible to minimize the impact of any negative reviews. Originality/value This study finds there is an asymmetric relationship between review valence (verbal) and numerical rating and considers brand strength to play an important moderating role. The authors have used real data from the TripAdvisor website, which allow people to express themselves in an unsolicited manner, and linked these with the results from the sentiment analysis.
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