From user-generated text to insight context-aware measurement of social impacts and interactions using natural language processing

Recent improvements in information and communication technologies have contributed to an increasingly globalized and connected world. The digital data that are created as the result of people's online activities and interactions consist of different types of personal and social information that can be used to extract and understand people's implicit or explicit beliefs, ideas, and biases. This thesis leverages methods and theories from natural language processing and social sciences to study and analyze the manifestations of various attributes and signals, namely social impacts, personal values, and moral traits, in user-generated texts. This work provides a comprehensive understanding of people's viewpoints, social values, and interactions and makes the following contributions. First, we present a study that combines review mining and impact assessment to provide an extensive discussion on different types of impact that information products, namely documentary films, can have on people. We first establish a novel impact taxonomy and demonstrate that, with a rigorous analysis of user-generated texts and a theoretically grounded codebook, classification schema, and prediction model, we can detect multiple types of (self-reported) impact in texts and show that people's language can help in gaining insights about their opinions, socio-cultural information, and emotional states. Furthermore, the results of our analyses show that documentary films can shift peoples' perceptions and cognitions regarding different societal issues, e.g., climate change, and using a combination of informative features (linguistic, syntactic, and psychological), we can predict impact in sentences with high accuracy. Second, we investigate the relationship between principles of human morality and the expression of stances in user-generated text data, namely tweets. More specifically, we first introduce and expand the Moral Foundations Dictionary and operationalize moral values to enhance the measurement of social effects. In addition, we provide detailed explanation on how morality and stance are associated in user-generated texts. Through extensive analysis, we show that discussions related to various social issues have distinctive moral and lexical profiles, and leveraging moral values as an additional feature can lead to measurable improvements in prediction accuracy of stance analysis. Third, we utilize the representation of emotional and moral states in texts to study people's interactions in two different social networks. Moreover, we first expand the analysis of structural balance to include direction and multi-level balance assessment (triads, subgroups, and the whole network). Our results show that analyzing different levels of networks and using various linguistic cues can grant a more inclusive view of people and the stability of their interactions; we found that, unlike sentiments, moral statuses in discussions stay balanced throughout the networks even in the presence of tension. Overall, this thesis aims to contribute to the emerging field of "social" NLP and broadens the scope of research in it by (1) utilizing a combination of novel taxonomies, datasets, and tools to examine user-generated texts and (2) providing more comprehensive insights about human language, cultures, and experiences

Movies, TV programs and Youtube channels

학위논문(박사) -- 서울대학교대학원 : 공과대학 산업공학과, 2021.8. 조성준.The content market, including video content market, is a high-risk, high-return industry. Because the cost of copying and distributing the created video content is very low, large profit can be generated upon success. However, as content is an experience good, its quality cannot be judged before purchase. Hence, marketing has an important role in the content market because of the asymmetry of information between suppliers and consumers. Additionally, it has the characteristics of One Source Multi Use; if it is successful, additional profits can be created through various channels. Therefore, it is important for the content industry to correctly distinguish content with a high probability of success from the one without it and to conduct effective marketing activities to familiarize consumers with the product. Herein, we propose a methodology to assist in data-based decision-making using machine learning models and help in identifying problematic issues in video content markets such as movies, TV programs, and over-the-top (OTT) market. In the film market, although marketing is very important, decisions are still made based on the sense of practitioners. We used the market research data collected through online and offline surveys to learn a model that can predict the number of audiences on the opening-week Saturday, and then use the learned model to propose a method for effective marketing activities. In the TV program market, programming is performed to improve the overall viewership by matching TV programs and viewer groups well. We learn a model that predicts the audience rating of a program using the characteristics of the program and the audience-rating information of the programs before, after, and at the same time, and use the resulting data to assist in decision-making to find the optimal programming scenario. The OTT market is facing a new problem of user's perception bias caused by the “recent recommendation” system. In the fields of politics and news particularly, if the user does not have access to different viewpoints because of the recommendation service, it may create and/or deepen a bias toward a specific political view without the user being aware of it. In order to compensate for this, it is important to use the recommended channel while the user is well aware of what kind of channel it is. We built a channel network in the news/political field using the data extracted from the comments left by users on the videos of each channel. In addition, we propose a method to compensate for the bias by classifying networks into conservative and progressive channel clusters and presenting the topography of the political tendencies of YouTube channels.1 Introduction 1 2 Prediction of Movie Audience on First Saturday with Decision Trees 5 2.1 Background 5 2.2 Related work 9 2.3 Predictive model construction 15 2.3.1 Data 15 2.3.2 Target variable 17 2.3.3 Predictor variable 19 2.3.4 Decision Tree and ensemble prediction models 28 2.4 Prediction model evaluation 29 2.5 Summary 37 3 Prediction of TV program ratings with Decision Trees 40 3.1 Background 40 3.2 Related work 42 3.2.1 Research on the ratings themselves 42 3.2.2 Research on broadcasting programming 44 3.3 Predictive model construction 45 3.3.1 Target variable 45 3.3.2 Predictor variable 46 3.3.3 Prediction Model 48 3.4 Prediction model evaluation 50 3.4.1 Data 50 3.4.2 Experimental results 51 3.5 Optimization strategy using the predictive model 54 3.5.1 Broadcasting programming change process 56 3.5.2 Case Study 57 3.6 Summary 60 4 Relation detection of YouTube channels 62 4.1 Background 62 4.2 Related work 65 4.3 Method 67 4.3.1 Channel representation 68 4.3.2 Channel clustering with large k and merging clusters by keywords 71 4.3.3 Relabeling with RWR 73 4.3.4 Isolation score 74 4.4 Result 74 4.4.1 Channel representation 74 4.4.2 Channel clustering with large k and merging clusters by keywords 76 4.4.3 Relabeling with RWR 77 4.4.4 Isolation score 79 4.5 Discussion 80 4.5.1 On the Representativeness of the Channel Preferences of the Users from Their Comments 80 4.5.2 On Relabeling with RWR 82 4.6 Summary 83 5 Conclusion 85 5.1 Contribution 85 5.2 Future Direction 87 Bibliography 91 국문초록 110박

The doctoral research abstracts. Vol:7 2015 / Institute of Graduate Studies, UiTM

Foreword: The Seventh Issue of The Doctoral Research Abstracts captures the novelty of 65 doctorates receiving their scrolls in UiTM’s 82nd Convocation in the field of Science and Technology, Business and Administration, and Social Science and Humanities. To the recipients I would like to say that you have most certainly done UiTM proud by journeying through the scholastic path with its endless challenges and impediments, and persevering right till the very end. This convocation should not be regarded as the end of your highest scholarly achievement and contribution to the body of knowledge but rather as the beginning of embarking into high impact innovative research for the community and country from knowledge gained during this academic journey. As alumni of UiTM, we will always hold you dear to our hearts. A new ‘handshake’ is about to take place between you and UiTM as joint collaborators in future research undertakings. I envisioned a strong research pact between you as our alumni and UiTM in breaking the frontier of knowledge through research. I wish you all the best in your endeavour and may I offer my congratulations to all the graduands. ‘UiTM sentiasa dihati ku’ / Tan Sri Dato’ Sri Prof Ir Dr Sahol Hamid Abu Bakar , FASc, PEng Vice Chancellor Universiti Teknologi MAR

Co-Nanomet: Co-ordination of Nanometrology in Europe

Nanometrology is a subfield of metrology, concerned with the science of measurement at the nanoscale level. Today’s global economy depends on reliable measurements and tests, which are trusted and accepted internationally. It must provide the ability to measure in three dimensions with atomic resolution over large areas. For industrial application this must also be achieved at a suitable speed/throughput. Measurements in the nanometre range should be traceable back to internationally accepted units of measurement (e.g. of length, angle, quantity of matter, and force). This requires common, validated measurement methods, calibrated scientific instrumentation as well as qualified reference samples. In some areas, even a common vocabulary needs to be defined. A traceability chain for the required measurements in the nm range has been established in only a few special cases. A common strategy for European nanometrology has been defined, as captured herein, such that future nanometrology development in Europe may build out from our many current strengths. In this way, European nanotechnology will be supported to reach its full and most exciting potential. As a strategic guidance, this document contains a vision for European nanometrology 2020; future goals and research needs, building out from an evaluation of the status of science and technology in 2010. It incorporates concepts for the acceleration of European nanometrology, in support of the effective commercial exploitation of emerging nanotechnologies. The field of nanotechnology covers a breadth of disciplines, each of which has specific and varying metrological needs. To this end, a set of four core technology fields or priority themes (Engineered Nanoparticles, Nanobiotechnology, Thin Films and Structured Surfaces and Modelling & Simulation) are the focus of this review. Each represents an area within which rapid scientific development during the last decade has seen corresponding growth in or towards commercial exploitation routes. This document was compiled under the European Commission Framework Programme 7 project, Co-Nanomet. It has drawn together input from industry, research institutes, (national) metrology institutes, regulatory and standardisation bodies across Europe. Through the common work of the partners and all those interested parties who have contributed, it represents a significant collaborative European effort in this important field. In the next decade, nanotechnology can be expected to approach maturity, as a major enabling technological discipline with widespread application. This document provides a guide to the many bodies across Europe in their activities or responsibilities in the field of nanotechnology and related measurement requirements. It will support the commercial exploitation of nanotechnology, as it transitions through this next exciting decade

Tag based Bayesian latent class models for movies : economic theory reaches out to big data science

For the past 50 years, cultural economics has developed as an independent research specialism. At its core are the creative industries and the peculiar economics associated with them, central to which is a tension that arises from the notion that creative goods need to be experienced before an assessment can be made about the utility they deliver to the consumer. In this they differ from the standard private good that forms the basis of demand theory in economic textbooks, in which utility is known ex ante. Furthermore, creative goods are typically complex in composition and subject to heterogeneous and shifting consumer preferences. In response to this, models of linear optimization, rational addiction and Bayesian learning have been applied to better understand consumer decision- making, belief formation and revision. While valuable, these approaches do not lend themselves to forming verifiable hypothesis for the critical reason that they by-pass an essential aspect of creative products: namely, that of novelty. In contrast, computer sciences, and more specifically recommender theory, embrace creative products as a study object. Being items of online transactions, users of creative products share opinions on a massive scale and in doing so generate a flow of data driven research. Not limited by the multiple assumptions made in economic theory, data analysts deal with this type of commodity in a less constrained way, incorporating the variety of item characteristics, as well as their co-use by agents. They apply statistical techniques supporting big data, such as clustering, latent class analysis or singular value decomposition. This thesis is drawn from both disciplines, comparing models, methods and data sets. Based upon movie consumption, the work contrasts bottom-up versus top-down approaches, individual versus collective data, distance measures versus the utility-based comparisons. Rooted in Bayesian latent class models, a synthesis is formed, supported by the random utility theory and recommender algorithm methods. The Bayesian approach makes explicit the experience good nature of creative goods by formulating the prior uncertainty of users towards both movie features and preferences. The latent class method, thus, infers the heterogeneous aspect of preferences, while its dynamic variant- the latent Markov model - gets around one of the main paradoxes in studying creative products: how to analyse taste dynamics when confronted with a good that is novel at each decision point. Generated by mainly movie-user-rating and movie-user-tag triplets, collected from the Movielens recommender system and made available as open data for research by the GroupLens research team, this study of preference patterns formation for creative goods is drawn from individual level data

Media’s influence on the 21st century society: A global criminological systematic review

This investigation assumes that the media can reduce or spread criminal activities and tendencies based on how the concerned parties apply the policies and community standards that guide these platforms’ use. In total, 254 materials were gathered across several search systems between October 2021 and September 2022. Qualitative data were used from the selected materials to synthesise and summarise the content on the examined 21st-century events and media’s influence on crime. It is not possible to reject the premise that the media influences opinions on crime and the legal system. Nevertheless, the data reveals that no causal media effect can be directly established. However, the same data uncovers how media portrays an activity affects how people perceive it. Advances in technology, media, and criminology may have affected the analysis of records, including the time and quality of resources. More accurate and fair media coverage of crime would lead to a more informed and aware population. On the other hand, media houses that promote and reward good behaviour should be applauded. These two steps ensure the media cannot be ignored when assessing crime and how the public perceives it, as it can encourage crime and shift perceptions. Therefore, further research, stricter laws and policies, and community education on crime prevention and media screening are needed. The fact that unfavourable media coverage of crime can ruin a business, either directly or indirectly (consumer behaviour changes due to crime), makes this paper of utmost importance for businessmen, politicians, and local agencies.Esta dissertação presume que os media podem ser utilizados para reduzir ou difundir atividades ou tendências criminosas, dependendo da aplicação de políticas e padrões comunitários que influenciam tais plataformas. Foram utilizados 254 materiais reunidos em diversos sistemas de pesquisa entre outubro de 2021 e setembro de 2022. Estes compreendem publicações do século XXI que examinam a influência dos media nas práticas criminais e suas perceções. Apesar deste estudo não possibilitar estabelecer uma relação causal, não é, ainda assim, possível rejeitar a premissa de que os media influenciam as perceções face ao crime. Determina, contudo, que o modo como os media divulgam uma atividade afeta a perceção social face à mesma. Uma população mais informada e consciente depende de uma cobertura mediática mais fatual. Os media que promovem e recompensam o bom comportamento devem ser louvados. Os media não podem ser ignorados na avaliação do crime e da sua perceção, tendo o poder de incentivar a criminalidade e potenciar alterações nas perceções sociais. Consequentemente, é necessário investigar mais, aplicar leis e políticas mais rigorosas, e investir em programas de educação comunitária de prevenção à criminalidade e interpretação dos media. Esta dissertação é de elevada importância a empresários, políticos e outros órgãos locais, pelo fato de a cobertura desfavorável do crime pelos media poder arruinar um indivíduo, organização ou até um negócio, seja de forma direta (críticas ao estabelecimento) ou indireta (mudanças no comportamento do consumidor devido à ocorrência de crimes numa região)

The Evolution of Substance Use Coverage in the Philadelphia Inquirer

The media's representation of illicit substance use can lead to harmful stereotypes and stigmatization for individuals struggling with addiction, ultimately influencing public perception, policy, and public health outcomes. To explore how the discourse and coverage of illicit drug use changed over time, this study analyzes 157,476 articles published in the Philadelphia Inquirer over a decade. Specifically, the study focuses on articles that mentioned at least one commonly abused substance, resulting in a sample of 3,903 articles. Our analysis shows that cannabis and narcotics are the most frequently discussed classes of drugs. Hallucinogenic drugs are portrayed more positively than other categories, whereas narcotics are portrayed the most negatively. Our research aims to highlight the need for accurate and inclusive portrayals of substance use and addiction in the media

The visual communication of environmental awareness issues in Jeff Orlowski's,Chasing Ice (2012) and Yann Arthurs -Bertrand's home (2009)

This study presents an investigation into the visual communication complexities within the genre of documentary film, specifically aimed at the development of a set of criteria of cinematic techniques for the visual communication of environmental awareness issues. This process utilises a theoretical approach to understanding the development and communicative possibilities of documentary film, as well as an analytical interpretation structured on semiotic film theory. The theoretical investigation reveals Bill Nichols’ (2010) documentary modes as an established analytical model. This study engages with four of Nichols’ six modes – namely, the poetic, the expository, the observational and the participatory modes, as the criteria for the extraction of scenes and/or images from Chasing Ice (2012) by Jeff Orlowski and Home (2009) by Yann Arthurs-Bertrand. Once Nichols’ modes have been identified, a semiotic reading is conducted. Gillian Rose’s (2016) visual analysis framework underpinned by Pieter J. Fourie’s (1988) sociological approach to film analysis, is utilised to read the selected film texts. A comparative analysis of Chasing Ice (2012) and Home (2009) reveals that the inclusion of different and multiple modes constructs the visualisation of environmental awareness issues in the documentary film genre. The cinematic techniques specific to the documentary modes represented in Chasing Ice (2012) and Home (2009) are appropriated in the construction of three film shorts within the researcher’s documentary film study, Karoo (2017). This combination of theory and practice yields the researcher a considered and informed approach to constructing documentary imagery aimed at visualising the current environment of the Karoo Basin prior to the possibility of shale gas exploration and/or exploitation