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In the last years, social networks have increased in active members who upload and share postings about daily activities (pictures, comments, news, likes etc.), but also use these networks to get informed. During a crisis situation, the occurrence of an unexpected event can generate immediate reactions from active members, which further result in a...
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Die Digitalisierung hebt die Lüge auf eine neue Ebene. Ausgewiesene Forscherinnen und Forscher legen mit diesem Band ihre umfassenden Analyseergebnisse vor, die sie bezüglich digitaler Desinformation in einem interdisziplinären Ansatz gewonnen haben: Was macht Desinformation im deutschsprachigen Internet aus? Wie wirkt Desinformation? Wie kann sie...
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... On the other hand, SBI presents the combination of corporate data with UGC for decision-makers to improve their business based on the trends perceived from the environment (Gallinucci, Golfarelli and Rizzi, 2015). Șușnea and Iftene (2018) state that SOCMINT is a recently coined term for the confluence of ideas from Open Source Intelligence (OSINT) and web mining techniques (machine learning and database methods) applied to social media data in order to identify and understand those situations from social media environments characterised by the behaviour of individuals that would affect national security, and accordingly try to make rational decisions to bring the situation to the desired state. Park, Choi and Rho (2016) argue that governments should utilise social media as a channel for government service provision and communication, while considering the diversity of characteristics and risks that are inherent in social media. ...
Citizen Relationship Management (CzRM) can improve governmental service delivery and offer citizens an opportunity for e-participation and collaboration and improved service delivery. Social Media Analytics (SMA) holds the potential to provide a decision making framework that can measure the activities of citizens from social media data and thereby facilitate CzRM. However, the benefits and potential applications of SMA are rarely realised by governments. The purpose of this paper is to critically analyse literature to classify the benefits and applications of SMA as a potential solution for supporting CzRM. Grounded theory was used to identify core categories related to SMA and the relationships between categories. These were then analysed in more detail to compile a classification of six main categories of benefits of SMA to government, with several related applications. The benefits are 1) improved CzRM and service delivery; 2) improved decision making; 3) transparency, engagement and Open Government Data (OGD); 4) improved data management and quality; 5) data analysis and intelligence; and 6) data value for innovation. The analysis of SMA benefits and applications can be used to assist governments with planning SMA projects and to ensure the greatest opportunity for success. Researchers can use the findings to undergird further empirical research related to SMA particularly in the context of e-participation, decision making in government and CzRM.
Globally social media has shown unprecedented levels of adoption and Social Media Analytics (SMA) is a rapidly growing topic. For governments, SMA holds the promise of providing tools and frameworks to collect, monitor, analyse and visualise social media data, usually driven by specific requirements from a target application. However, social media data is noisy and unstructured, and organisations struggle to extract knowledge from this data, and convert it into actual intelligence. This study argues that SMA can support intelligent decision-making for Citizen Relationship Management (CzRM). CzRM is a growing effort of governments around the world to strive to respond rapidly to their citizens by fostering a closer relationship thereby creating more effective and efficient service delivery. However, there is a little evidence in literature on empirical studies of any existing decision-making framework for CzRM and SMA adoption. In particular, there is a gap with regards incorporating SMA into decision-making for CzRM of governments, particularly in developing countries like South Africa.
The aim of this study was to develop a framework that provides guidelines, including methods and tools, incorporating SMA into decision-making for CzRM in the Gauteng Provincial Government (GPG) and the Free State Provincial Government (FSPG) of South Africa. A Systematic Literature Review (SLR) and conceptual analysis method was conducted to design the Social Media Analytics Framework for Decision-making in the context of CzRM (the SMAF). The findings from the literature review revealed several benefits and challenges with SMA, in particular the shortage of skills, guidelines, methods and tools for SMA. These challenges were used to draft guidelines that were included in the framework, which consists of five components that can be used to derive intelligent information from SMA.
The pragmatic philosophy and a case study design was used to generate an in-depth, multi-faceted understanding of the underlying problems in the case of the GPG and the FSPG. The German North-West Metropolitan region was used as a third case study to provide a more global perspective and a case of a developed country in terms of Gross Domestic Product. The scope of the study was limited to social media posts by provincial citizens related to CzRM and service delivery. Both formative and summative evaluations of the proposed theoretical framework were conducted. The formative evaluation was conducted as an Expert Review to receive feedback of the framework from the experts in the field of Computer Science and Information Systems. The findings validated the framework and some minor improvements were made based on the experts’ recommendations. Focus Group Discussions (FGDs) with participants from government managers and decision makers in the three cases were conducted. Case documents for the three cases were collected and reviewed. All collected data was analysed using the Qualitative Content Analysis (QCA) method and common categories and themes were identified.
Summative evaluations were conducted in the form of a Field Study, which consisted of an analysis of Twitter data from the three cases, and a closing FGD with Business Intelligence (BI) experts at the primary case of the e-Government department of the GPG. The findings revealed that SMA has been adopted in all three cases; however, while their strategies are comprehensive their implementations are very much in their early stages. The findings also highlighted the status of SMA in government and some potential gaps and areas for implementing the framework.
Keywords: Decision-making, Big Data, Social Media Analytics, Citizen Relationship Management, Service Delivery
Social Media Analytics (SMA) has brought new improvement and development opportunities to aid decision-making for government and to support e-governance and smart city projects such as Citizen Relationship Management (CzRM). The purpose of this paper is to report on the expert review interviews conducted to verify the Social Media Analytics Framework (SMAF) for CzRM. This framework was designed based on the Systematic Literature Review (SLR) approach. The expert review consisted of online interviews with five experts from the field of Computer Science and Information Systems (IS). Qualitative Content Analysis (QCA) using Atlas.ti was conducted to organize the data, facilitate coding and identify themes. The findings from the review verified the five components of the framework, which are: Success factors and guidelines for SMA; The research domain of CzRM; The data process phases and methods; Methods and tools for SMA; and Decision-making and Social Media Intelligence (SOCMINT). Future work will further validate the framework through focus group discussions and an extant systems analysis.KeywordsCitizen relationship managementData value chainDecision-makinge-governanceExpert reviewSocial media analyticsSocial media intelligence
Social media is a cybersecurity risk for every business. What do people share on the Internet? Almost everything about oneself is shared: friendship, demographics, family, activities and work-related information. This could become a potential risk in every business if the organisation’s policies, training and technology fail to properly address these issues. In many cases, it is the employees’ behaviour that can put key company information at danger. Social media has turned into a reconnaissance tool for malicious actors and users accounts are now seen as a goldmine for cyber criminals. Investigation of social media is in the embryonic stage and thus is not yet well understood. This research project aims to collect and analyse open-source data from LinkedIn, discover data leakage and analyse personality types through software as a service (SAAS). The final aim of the study is to understand if there are behavioural factors that can predict one’s attitude towards disclosing sensitive data.
Social Media is a cyber-security risk for every business. What do people share on the Internet? Almost everything about oneself is shared: friendship, demographics, family, activities, and work-related information. This could become a potential risk in every business if the organization's policies, training and technology fail to properly address these issues. In many cases, it is the employees' behaviour that can put key company information at danger. Social media has turned into a reconnaissance tool for malicious actors and users accounts are now seen as a goldmine for cyber criminals. Investigation of Social Media is in the embryonic stage and thus, is not yet well understood. This research project aims to collect and analyse open-source data from LinkedIn, discover data leakage and analyse personality types through software as a service (SAAS). The final aim of the study is to understand if there are behavioral factors that can predicting one's attitude toward disclosing sensitive data.
