BlogForever D2.6: Data Extraction Methodology

This report outlines an inquiry into the area of web data extraction, conducted within the context of blog preservation. The report reviews theoretical advances and practical developments for implementing data extraction. The inquiry is extended through an experiment that demonstrates the effectiveness and feasibility of implementing some of the suggested approaches. More specifically, the report discusses an approach based on unsupervised machine learning that employs the RSS feeds and HTML representations of blogs. It outlines the possibilities of extracting semantics available in blogs and demonstrates the benefits of exploiting available standards such as microformats and microdata. The report proceeds to propose a methodology for extracting and processing blog data to further inform the design and development of the BlogForever platform

Opinion mining and sentiment analysis in marketing communications: a science mapping analysis in Web of Science (1998–2018)

Opinion mining and sentiment analysis has become ubiquitous in our society, with applications in online searching, computer vision, image understanding, artificial intelligence and marketing communications (MarCom). Within this context, opinion mining and sentiment analysis in marketing communications (OMSAMC) has a strong role in the development of the field by allowing us to understand whether people are satisfied or dissatisfied with our service or product in order to subsequently analyze the strengths and weaknesses of those consumer experiences. To the best of our knowledge, there is no science mapping analysis covering the research about opinion mining and sentiment analysis in the MarCom ecosystem. In this study, we perform a science mapping analysis on the OMSAMC research, in order to provide an overview of the scientific work during the last two decades in this interdisciplinary area and to show trends that could be the basis for future developments in the field. This study was carried out using VOSviewer, CitNetExplorer and InCites based on results from Web of Science (WoS). The results of this analysis show the evolution of the field, by highlighting the most notable authors, institutions, keywords, publications, countries, categories and journals.The research was funded by Programa Operativo FEDER Andalucía 2014‐2020, grant number “La reputación de las organizaciones en una sociedad digital. Elaboración de una Plataforma Inteligente para la Localización, Identificación y Clasificación de Influenciadores en los Medios Sociales Digitales (UMA18‐ FEDERJA‐148)” and The APC was funded by the same research gran

NOTES2: Networks-of-Traces for Epidemic Spread Simulations

Decision making and intervention against infectious diseases require analysis of large volumes of data, including demographic data, contact networks, agespecific contact rates, mobility networks, and healthcare and control intervention data and models. In this paper, we present our Networks-Of-Traces for Epidemic Spread Simulations (NOTES2) model and system which aim at assisting experts and helping them explore existing simulation trace data sets. NOTES2 supports analysis and indexing of simulation data sets as well as parameter and feature analysis, including identification of unknown dependencies across the input parameters and output variables spanning the different layers of the observation and simulation data

Spillover Effects of Management Companies in the Vtuber Market

학위논문(석사) -- 서울대학교대학원 : 경영대학 경영학과, 2021.8. 윤혜리.Increasing usage of social media has given subsequent birth to micro-celebrities, or social media influencers (SMIs). Despite the fact that SMIs function as key opinion-leaders in society and the market, little is known about what traits make an SMI popular in the first place. While SMIs are generally considered to gain popularity from rock-bottom through individual endeavors alone, we find an exceptional media sector consisting of virtual YouTubers (vtubers). A vtuber, unlike the usual human YouTuber, is an artificially created figure strictly managed by sponsoring companies from the beginning of his/her debut. Finding a similarity between sponsor-vtuber relationships and parent-child relationships within brand extensions, we ran a random effects model against 560 company-owned vtubers to check whether similar spillover effects can be observed in a social media context as well. Our research yielded positive results, suggesting the existence of persistent spillover effects based on parent-brand popularity. An additional time series analysis was conducted against the weekly changes in the size of management agency influence on their affiliated vtubers. An ARIMA(1,2,0) model demonstrates a high fit with our data, and we find that the model confirms a constantly decreasing size of influence along with the passage of time.소셜미디어의 확산은 마이크로셀레브리티와 소셜미디어 인플루언서(SMI)의 등장을 초래했다. 이미 사회적, 경제적으로 SMI들이 오피니언 리더로서 큰 영향력을 행사하고 있음에도 불구하고 이들이 정확히 어떤 근본적 요인으로 인해 대중적 인기를 얻게 되었는지에 대해 알려진 바는 많지 않다. 많은 경우에 SMI들이 순수하게 자력으로만 팬덤을 구축하는 것으로 간주되는 것에 반해, 필자들은 버츄얼 유튜버(vtuber) 업계로부터 예외적인 상황을 목격했다. 일반적인 인간 유튜버와 달리, vtuber는 데뷔 이전부터 소속사로부터 엄격하게 관리당하고 통제 받는 가상의 디지털 캐릭터들이다. 본 연구에서는 소속사 대 vtuber의 관계가 브랜드 확장 상태의 모브랜드 대 신규 브랜드의 관계와 유사하다는 점에 착안하여, 후자의 경우에 관찰되는 스필오버 효과가 전자에서도 발현되는지 검증하기 위해 소속사와 계약을 맺고 있는 총 560 명의 vtuber에 대해 임의효과 모형을 적용시킨다. 그 결과, 소속사의 영향력이 vtuber의 인기에 대해 긍정적 스필오버 효과가 있음이 확인되었다. 또, 주차별 스필오버 효과 크기의 변화에 대한 시계열 분석을 통해 추세를 예측하는 데 적합한 모형으로 ARIMA(1,2,0) 모델을 특정해내어 시간이 지남에 따라 스필오버 효과가 감소하는 경향성을 지님을 검증했다.Chapter 1. Introduction 1 Chapter 2. Literature Review 3 Chapter 3. Research Model and Hypotheses 14 Chapter 4. Data Analysis and Methodology 18 Chapter 5. Results 21 Chapter 6. Discussion and Conclusion 29 Bibliography 32 Abstract in Korean 41 Appendices 42석

Sponsored messaging about climate change on Facebook: Actors, content, frames

Online communication about climate change is central to public discourse around this contested issue. Facebook is a dominant social media platform known to be a major source of information and online influence, yet discussion of climate change on the platform has remained largely unstudied due to difficulties in accessing data. This paper utilises Facebook's repository of social/political ads to study how climate change is framed as an issue in adverts placed by different actors. Sponsored content is a strategic investment and presumably intended to be persuasive, so patterns of who pays for adverts and how those adverts frame the issue can reveal large-scale trends in public discourse. We show that most money spent on climate-related messaging is targeted at users in the US, GB and CA. While the number of advert impressions correlates with total spend by an actor, there is a secondary effect of unpaid social sharing which can substantially affect the number of impressions per dollar spent. Most spend in the US is by political actors, while environmental non-governmental organisations dominate spend in GB. Analysis shows that climate change solutions are well represented in GB, while climate change impacts such as extreme weather events are strongly represented in the US and CA. Different actor types frame the issue of climate change in different ways; political actors position the issue as party political and a point of difference between candidates, whereas environmental NGOs frame climate change as the focus of collective action and social mobilisation. Overall, our study provides a first empirical exploration of climate-related advertising on Facebook. It shows the diversity of actors seeking to use Facebook as a platform for their campaigns and how they utilise different topic frames to persuade users to act.Comment: 44 pages, 9 figure

Diversity of thought in the blogosphere: implications for influencing and monitoring image

A blog, a shortened form of weblog, is a website where an author shares thoughts in posts or entries. Most blogs permit readers to add comments to posts and thereby be a conversational mechanism. One way that companies have started to use blogs is to monitor their corporate image (in this dissertation, the term image is used in reference to corporate, brand and/or product image). This study focuses on how common socio-psychological processes mediate consumers’ revelation of corporate image in the blogosphere. Centering resonance analysis, a means of measuring similarity between two bodies of text, is used in conjunction with multidimensional scaling to locate text as cognitive objects in a space. Clusters are then detected and measured to quantify diversity in the thoughts expressed. Detected patterns are studied from a social process theory perspective, where complex phenomena are hypothesized to be the result of the interaction of simpler processes. A majority of blog commenters compromise the expression of their thoughts to gain social acceptance. This study identifies the most extreme of such people so companies who monitor blogs can assign less weight to image indications gained from them as they may be merely expressing thoughts that are intended to maintain social acceptance. It was also found that single-theme blogs attract a readership with similarly narrow interests. The boldest and most diverse thinkers among comment writers have the most impact because of their ability to provoke the thinking of others. However, commenters who repeat the same ideas have little effect, suggesting that introducing shills is unlikely to shift the sentiment of a blog’s readership. People participate in blog communities for reasons (e.g., need for community) that may undermine thought diversity. However, there may be value in serving those needs even though no valuable insights are provided into image or directions for product development. Members of homogeneous-thinking communities were observed to more actively participate, with greater longevity. This may increase loyalty to the company hosting the blog

The Political Potency of Tibetan Identity in Pop Music and Dunglen

Since their beginnings in the 1980s, Tibetan pop music and dunglen (lute songs of northeastern Tibet) have shown strong expressions of Tibetan identity. They also represent a flourishing area of Tibetan language cultural production. This is significant after the repetitive propaganda songs of the Cultural Revolution and given the pressures and restrictions in Tibet on language and religion in particular. However, in this article, I critique straightforward interpretations of the Tibetanness of Tibetan popular music as representing a zone of assertion or resistance, arguing instead that the political potency of Tibetan pop music and dunglen is far more double-edged, coopted and complex. Drawing on ethnography, I describe how state institutions and largely Tibetan cultural workers have in fact played the leading role in its genesis and production and are still a powerful force in its production and dissemination. Moreover, while it is often said that the state is against Tibetan identity and culture, in fact, the attitude is far more ambivalent and contradictory, with China a unitary multi-ethnic state where 55 minority nationalities with distinct culture and identity are recognized, including Tibetans. I argue through the analysis of song lyrics that expressions of Tibetan identity per se are not censored; rather, it is when these expressions are linked to particular political demands. As I explore, a number of reasons can be identified as to why the state does not censor Tibetan pop music and dunglen more harshly, and furthermore, there are reasons why Tibetan language assertion has had so much more success in the realm of pop music than it has had in schools

Evaluation of Graph Sampling: A Visualization Perspective

Graph sampling is frequently used to address scalability issues when analyzing large graphs. Many algorithms have beenproposed to sample graphs, and the performance of these algorithms has been quantified through metrics based on graph structuralproperties preserved by the sampling: degree distribution, clustering coefficient, and others. However, a perspective that is missing isthe impact of these sampling strategies on the resultant visualizations. In this paper, we present the results of three user studies thatinvestigate how sampling strategies influence node-link visualizations of graphs. In particular, five sampling strategies widely used inthe graph mining literature are tested to determine how well they preserve visual features in node-link diagrams. Our results showthat depending on the sampling strategy used different visual features are preserved. These results provide a complimentary view tometric evaluations conducted in the graph mining literature and provide an impetus to conduct future visualization studie