Adopting microblogging solutions for interaction with government

Authorities in the People’s Republic of China communicate with citizens using an estimated 600,000 Sina Weibo microblogs. This study reports on a study of Chinese citizens’ adoption of microblogs to interact with the government. Adoption results from trust and peer pressure in smaller-network ties (densely knit, pervasive social networks surrounding individual citizens). Larger-network ties (trust in institutions at large, such as the Chinese Communist Party, executive organizations, the judicial system, the media, etc.) are not associated with the adoption of microblogging. Furthermore, higher levels of anxiety are correlated with lower levels of use intention, and this finding underlines the impact of the Chinese authority’s surveillance and control activities on the lives of individual Chinese citizens. Based on these findings, we outline a theory of why citizens use microblogs to interact with the government and suggest avenues for further research into microblogs, state–citizen communication patterns and technology adoption

Trust, fear and social influence: on the use of social media in China’s authoritarian governance regime

This paper reports on the analysis of results of a survey among Chinese citizens about their intended use of social media to interact with government agencies and associated motivations. Citizens’ use intentions were found to be correlated with citizens’ trust in officials, social influence (peer pressure) and anxiety, but not with trust in government. These results provide building blocks for an explanatory theory of citizens’ use of social media to interact with government, especially in an authoritarian regime like China’s system of public governance. This explanatory theory is consistent with an institutional perspective on technology use, in which use intentions and behaviours are explained by norms, practices and taken-for-granted assumptions, rather than by rational cost-benefit considerations. The paper is concluded with recommendations for comparative research on antecedents of social media in government-citizen relations in various governance systems

Automated Assessment of the Aftermath of Typhoons Using Social Media Texts

Disasters are one of the major threats to economics and human societies, causing substantial losses of human lives, properties and infrastructures. It has been our persistent endeavors to understand, prevent and reduce such disasters, and the popularization of social media is offering new opportunities to enhance disaster management in a crowd-sourcing approach. However, social media data is also characterized by its undue brevity, intense noise, and informality of language. The existing literature has not completely addressed these disadvantages, otherwise vast manual efforts are devoted to tackling these problems. The major focus of this research is on constructing a holistic framework to exploit social media data in typhoon damage assessment. The scope of this research covers data collection, relevance classification, location extraction and damage assessment while assorted approaches are utilized to overcome the disadvantages of social media data. Moreover, a semi-supervised or unsupervised approach is prioritized in forming the framework to minimize manual intervention. In data collection, query expansion strategy is adopted to optimize the search recall of typhoon-relevant information retrieval. Multiple filtering strategies are developed to screen the keywords and maintain the relevance to search topics in the keyword updates. A classifier based on a convolutional neural network is presented for relevance classification, with hashtags and word clusters as extra input channels to augment the information. In location extraction, a model is constructed by integrating Bidirectional Long Short-Time Memory and Conditional Random Fields. Feature noise correction layers and label smoothing are leveraged to handle the noisy training data. Finally, a multi-instance multi-label classifier identifies the damage relations in four categories, and the damage categories of a message are integrated with the damage descriptions score to obtain damage severity score for the message. A case study is conducted to verify the effectiveness of the framework. The outcomes indicate that the approaches and models developed in this study significantly improve in the classification of social media texts especially under the framework of semi-supervised or unsupervised learning. Moreover, the results of damage assessment from social media data are remarkably consistent with the official statistics, which demonstrates the practicality of the proposed damage scoring scheme

Innovative big data integrationand analysis techniques for urban hazard management

PhD ThesisModern early warning systems (EWS) require sophisticated knowledge of natural hazards, the urban context and underlying risk factors to enable dynamic and timely decision making (e.g., hazard detection, hazard preparedness). Landslides are a common form of natural hazard with a global impact and are closely linked to a variety of other hazards. EWS for landslide prediction and detection relies on scienti c methods and models which require input from the time-series data, such as the earth observation (EO) and ancillary data. Such data sets are produced by a variety of remote sensing satellites and Internet of Things sensors which are deployed in landslide-prone areas. Besides, social media-based time-series data has played a signi cant role in modern disaster management. The emergence of social media has led to the possibility of the general public contributing to the monitoring of natural hazard by reporting incidents related to hazard events. To this end, the data integration and analysis of potential time-series data sources in EWS applications have become a challenge due to the complexity and high variety of data sources. Moreover, sophisticated domain knowledge of natural hazards and risk management are also required to enable dynamic and timely decision making about serious hazards. In this thesis, a comprehensive set of algorithmic techniques for managing high varieties of time series data from heterogeneous data sources is investigated. A novel ontology, namely Landslip Ontology, is proposed to provide a knowledge base that establishes the relationship between landslide hazard and EO and ancillary data sources to support data integration for EWS applications. Moreover, an ontology-based data integration and analytics system that includes human in the loop of hazard information acquisition from social media is proposed to establish a deeper and more accurate situational awareness of hazard events. Finally, the system is extended to enable an interaction between natural hazard EWS and electrical grid EWS to contribute to electrical grid network monitoring and support decision-making for electrical grid infrastructure management

Deliberative democracy via cyberspace : A study of online political forums in Taiwan

The emergence of the Internet ignited new hope for those aspiring to reinvigorate democracy, especially online political forums whose discursive nature seemingly offers the possibility of deliberative democracy. This thesis aims to explore whether online political forums are capable of contributing to public deliberation in Taiwan's context. Three forums have been chosen in this study, Yahoo Political Forum, Palm BBS and The Presidential Office Forum, respectively sponsored by a commercial website, an academic institution and the government. The complete research project has two branches of inquiry, one focuses on the analysis of the messages published in the forums, and the other aims to comprehend online discussants' motivations, expectations and standpoints concerning online deliberation. Drawing on systematic content analysis and discourse analysis, the results reveal that 1) the discursive qualities are different amongst the three forums The Presidential Office's discussants tend to create their own topics, in contrast to the participants of Yahoo and Palm who rely very much on journalists' reports as sources of discussion topics 2) Current political tensions are amplified, and engender verbal conflict in Yahoo and Palm which thwarts the rationality of discussions 4) Driven by political efficacy, the participants in The Presidential Office prefer to communicate directly with bureaucrats. The analytic results from the in-depth interviews show that the discussants are encouraged and motivated to participate by the forums' anonymous character nevertheless, the lack of positive responses and encouragements gained from the extended environment causes the discussants to reward themselves by pleasing their individual demands. Public deliberation in online forums may be weakened by unequal access, irrational participants/actions and fragmentation of public discourse. In this study, online political forums do not yet constitute a virtual/alternative public sphere. Their deliberative function confronts identity politics and tensions between political groups, therefore, to talk politics online the boundaries and differences of the political diversity in Taiwan must be overcome