Raising and Rising Voices in Social Media - A Novel Methodological Approach in Studying Cyber-Collective Movements

Emerging cyber-collective social movements (CSMs) have frequently made headlines in the news. Despite their popularity, there is a lack of systematic methodologies to empirically study such movements in complex online environments. Using the Al-Huwaider online campaign as a case to illustrate our methodology, this contribution attempts to establish a rigorous and fundamental analysis that explains CSMs. We collected 150 blogs from 17 countries ranging between April 2003 and July 2010 with a special focus on Al-Huwaider’s campaigns capturing multi-cultural aspects for our analysis. Bearing the analysis upon three central tenets of individual, community, and transnational perspectives, we develop novel algorithms modeling CSMs by utilizing existing collective action theories and computational social network analysis. This article contributes a methodology to study the diffusion of issues in social networks and examines roles of influential community members. The proposed methodology provides a rigorous tool to understand the complexity and dynamics of CSMs. Such methodology also assists us in observing the transcending nature of CSMs with future possibilities for modeling transnational outreach. Our study addresses the lack of fundamental research on the formation of CSMs. This research contributes novel methodologies that can be applied to many settings including business, marketing and many others, beyond the exemplary setting chosen here for illustrative purposes

Building a High-Performing Collaborative Innovation Ecosystem in the Arctic

Global climate change, growing economic interest in the Arctic, and the inflow of investments into infrastructure in the Arctic regions have provided added impetus for the development of technology clusters and innovation ecosystems in the North and the Arctic. The goal of this study is to conceptually illustrate the roles of the actors involved in the development process of the innovation ecosystem in the Arctic regions. This research is crucial for optimizing the role of the actors responsible for the genesis of the innovation ecosystem in the Arctic regions and is based on a case study of the Yakutia innovation ecosystem. The Republic of Sakha (Yakutia) currently holds the leading position in the IT sphere of Far East Russia, accounting for 85% of the region’s IT services exports in the first quarter of 2020 and 82% in 2019. Yakutia develops the northernmost innovation ecosystem, with IT Park Yakutsk as its base, in collaboration with different actors from governments, universities, startup communities, and venture capital firms. This study applies a qualitative approach, with the data collection conducted using in-depth interviews. The interviewees in this study represent various actors, including businesses, governments, universities, and financial institutions. Theories developed by Dedehayir et al. (2018) and Tsujimoto et al. (2018) are used to explain and analyze the disposition, roles, and interactions of the actors during the genesis (birth phase) of the innovation ecosystem in the North. This study argues that building high-performing innovation ecosystems will produce digital and economic transformations that improve the sustainability and resilience of the societies in the Arctic.© 2021 The Authors and The Arctic Yearbook. Readers may download, distribute, photocopy, cite or excerpt this Arctic Yearbook material provided it is properly and fully credited however we do not allow commercial use or the making of derivatives.fi=vertaisarvioitu|en=peerReviewed

From past to present: spam detection and identifying opinion leaders in social networks

On microblogging sites, which are gaining more and more users every day, a wide range of ideas are quickly emerging, spreading, and creating interactive environments. In some cases, in Turkey as well as in the rest of the world, it was noticed that events were published on microblogging sites before appearing in visual, audio and printed news sources. Thanks to the rapid flow of information in social networks, it can reach millions of people in seconds. In this context, social media can be seen as one of the most important sources of information affecting public opinion. Since the information in social networks became accessible, research started to be conducted using the information on the social networks. While the studies about spam detection and identification of opinion leaders gained popularity, surveys about these topics began to be published. This study also shows the importance of spam detection and identification of opinion leaders in social networks. It is seen that the data collected from social platforms, especially in recent years, has sourced many state-of-art applications. There are independent surveys that focus on filtering the spam content and detecting influencers on social networks. This survey analyzes both spam detection studies and opinion leader identification and categorizes these studies by their methodologies. As far as we know there is no survey that contains approaches for both spam detection and opinion leader identification in social networks. This survey contains an overview of the past and recent advances in both spam detection and opinion leader identification studies in social networks. Furthermore, readers of this survey have the opportunity of understanding general aspects of different studies about spam detection and opinion leader identification while observing key points and comparisons of these studies.This work is supported in part by the Scientific and Technological Research Council of Turkey (TUBITAK) through grant number 118E315 and grant number 120E187. Points of view in this document are those of the authors and do not necessarily represent the official position or policies of TUBITAK.Publisher's VersionEmerging Sources Citation Index (ESCI)Q4WOS:00080858480001

Exploring and explaining participation in local opposition: brown coal mining in Horní Jiřetín

This book summarizes a three-year research project on local opposition to coal mining in the Northwestern part of the Czech Republic. The research focused on the relational dimensions of the opposition movement and the political context in which the movement operates

Marketing Applications of Social Tagging Networks

This dissertation focuses on marketing applications of social tagging networks. Social tagging is a new way to share and categorize content, allowing users to express their perceptions and feelings with respect to concepts such as brands and firms with their own keywords, “tags.” The associative information in social tagging networks provides marketers with a rich source of information reflecting consumers’ mental representations of a brand/firm/product. The first essay presents a methodology to create “social tag maps,” brand associative networks derived from social tags. The proposed approach reflects a significant improvement towards understanding brand associations compared to conventional techniques (e.g., brand concept maps and recent text mining techniques), and helps marketers to track real-time updates in a brand’s associative network and dynamically visualize the relative competitive position of their brand. The second essay investigates how information contained in social tags acts as proxy measures of brand assets that track and predict the financial valuation of firms using the data collected from a social bookmarking website, del.icio.us, for 61 firms across 16 industries. The results suggest that brand asset metrics based on social tags explain stock return. Specifically, an increase in social attention and connectedness to competitors is shown to be positively related to stock return for less prominent brands, while for prominent brands associative uniqueness and evaluation valence is found to be more significantly related to stock return. The findings suggest to marketing practitioners a new way to proactively improve brand assets for impacting a firm’s financial performance. The third essay investigates whether the position of products on social tagging networks can predict sales dynamics. We find that (1) books in long tail can increase sales by being strongly linked to well-known keywords with high degree centrality and (2) top sellers can be better sellers by creating dense content clusters rather than connecting them to well-known keywords with high degree centrality. Our findings suggest that marketing managers better understand a user community’s perception of products and potentially influence product sales by taking into account the positioning of their products within social tagging networks

Clinician-Led Improvement in Cancer Care (CLICC): Complementing Evidence-Based Medicine with Evidence-Based Implementation

This thesis explores whether a multifaceted intervention implemented through the NSW Agency for Clinical Innovation (ACI) Urology Clinical Network can improve the rates of referral of men with high-risk prostate cancer post-radical prostatectomy for consideration for adjuvant radiotherapy in line with clinical practice guideline recommended care. It comprises seven iterative studies that address urologists’ knowledge, attitudes and equipoise for the use of adjuvant radiotherapy for high-risk prostate cancer, the development of a clinical network embedded intervention and the evaluation of this intervention within a step-wedge cluster randomised trial ‘Clinician-Led Improvement in Cancer Care (CLICC)’ (NHMRC Partnership Grant 1011474; Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12611001251910). The thesis found some evidence that the CLICC intervention resulted in desired practice change. Results are presented within the context of the CLICC conceptual program logic framework and are interpreted in relation to knowledge, attitudes and beliefs in the wider urological community. The thesis concludes with consideration of how findings could be translated to the implementation of other clinical practice guideline recommendations