With the significant advancementstaking place in the last three decades in the field ofInformation Technology (IT), we are witnesses of an era unprecedented to the standards that mankind was used to, for centuries. Having access to a huge amount of dataalmost instantly,entails certainadvantages. One of which is the ability to observe in which segments of their expertise do scientists focus their research. That kind of knowledge, if properly appraised could hold the key to explaining what the new directions of the applied sciences will be and thus could help to constructing a “map” of the future developments from the Research and Development labs of the industries worldwide.Though the above statement may be considered too “futuristic”, already there have been documented attempts in the literature that have been fruitful into using vast amount of scientific data in an attempt to outline future scientific trends and thus scientific discoveries.The purpose of this research is to try to use a pioneeringmethodof modeling text corpora that already hasbeen used previously to the task of mapping the history of scientific discovery, that of Latent Dirichlet Allocation (LDA)and try to evaluate itsusability into detecting emerging research trends by the mere use of only the “Abstracts” from a collectionof scientific articles.To do that an experimental set is being utilized and the process is repeated over three experimental runs.The results, although not the ones that would validate the hypothesis, are showing that with certain improvements in the processing the hypothesis could be confirmed.

La structuration en thèmes est un domaine de recherche très prisé dans le traitement automatique du langage naturel car elle est le point de départ de plusieurs applications comme la recherche d’information, le résumé automatique et la modélisation des thèmes. Dans cette thèse, nous avons proposé un système de structuration automatique des journaux d’informations. Notre système contient deux modules : segmentation thématique et titrage. La segmentation thématique consiste à effectuer un pavage de l’émission en segments thématiquement homogènes. Ces derniers, sont généralement identifiés par des étiquettes anonymes, c’est alors le rôle du module de titrage d’affecter un titre à chaque segment.Ces travaux ont permis plusieurs contributions originales tel que l’exploitation conjointe de la distribution des mots et des locuteurs (cohésion de la parole) ainsi que l’utilisation des relations sémantiques de type diachronique. Après l’étape de segmentation, nous proposons d’apparier chaque segment avec les articles de presse du même jour. Le titre associé au segment est celui de l’article le plus proche thématiquement. Finalement, nous avons proposé deux nouvelles métriques d’évaluation, l’une pour la segmentation thématique et l’autre pour le titrage. Les expériences sont menées sur trois corpus caractérisés par leur richesse et leur diversité. Ils sont constitués de 168 journaux télévisés issus de 10 chaînes françaises transcrits automatiquement. / The topic structuring is an area that has attracted much attention in the Natural Language Processing community. Indeed, topic structuring is considered as the starting point of several applications such as information retrieval, summarization and topic modeling.In this thesis, we proposed a generic topic structuring system i.e. that has the ability to deal with any TV Broadcast News.Our system contains two steps: topic segmentation and title assignment. Topic segmentation consists in splitting the document into thematically homogeneous fragments. The latter are generally identified by anonymous labels and the last step has to assign a title to each segment.Several original contributions are proposed like the use of a joint exploitation of the distribution of speakers and words (speech cohesion) and also the use of diachronic semantic relations. After the topic segmentation step, the generated segments are assigned a title corresponding to an article collected from Google News during the same day. Finally, we proposed the evaluation of two new metrics, the first is dedicated to the topic segmentation and the second to title assignment.The experiments are carried out on three corpora. They consisted of 168 TV Broadcast News from 10 French channels automatically transcribed. Our corpus is characterized by his richness and diversity.

This dissertation describes WikiRank, an unsupervised method of assigning relative values to elements of a broad coverage encyclopedic information source in order to identify those entries that may be relevant to a given piece of text. The valuation given to an entry is based not on textual similarity but instead on the links that associate entries, and an estimation of the expected frequency of visitation that would be given to each entry based on those associations in context. This estimation of relative frequency of visitation is embodied in modifications to the random walk interpretation of the PageRank algorithm. WikiRank is an effective algorithm to support natural language processing applications. It is shown to exceed the performance of previous machine learning algorithms for the task of automatic topic identification, providing results comparable to that of human annotators. Second, WikiRank is found useful for the task of recognizing text-based paraphrases on a semantic level, by comparing the distribution of attention generated by two pieces of text using the encyclopedic resource as a common reference. Finally, WikiRank is shown to have the ability to use its base of encyclopedic knowledge to recognize terms from different ontologies as describing the same thing, and thus allowing for the automatic generation of mapping links between ontologies. The conclusion of this thesis is that the "knowledge access heuristic" is valuable and that a ranking process based on a large encyclopedic resource can form the basis for an extendable general purpose mechanism capable of identifying relevant concepts by association, which in turn can be effectively utilized for enumeration and comparison at a semantic level.

Orientador: Anna Christina Bentes da Silva / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Estudos da Linguagem / Made available in DSpace on 2018-08-18T14:52:08Z (GMT). No. of bitstreams: 1 Granato_LiviaBertolazzi_M.pdf: 5909052 bytes, checksum: 1133fc07d0e787bc56aa2b1db44fc41c (MD5) Previous issue date: 2011 / Resumo: O objetivo deste trabalho é o de compreender os aspectos de inovação, manipulação e mudança do gênero programa de auditório. Para tanto, as análises se dedicam a descrever e a comparar dois programas de auditório: Manos e Minas e Altas Horas. Pretendemos saber quais são os aspectos de inovação, manipulação e mudança desse gênero e de que maneira estabilidade e inovação encontram-se articulados de forma a colaborar para uma melhor compreensão da natureza relativamente estável dos gêneros do discurso. Com base na articulação entre as teorias sobre os gêneros discursivos e as teorias sobre os gêneros multimodais, privilegiamos a descrição e a análise da estrutura geral dos programas e das temáticas privilegiadas por cada um. Manos e Minas tem o objetivo de trazer 'a voz da periferia' à mídia televisiva com vistas à valorização das práticas dessa comunidade e Altas Horas o de entrevistar personalidades públicas e interagir com os sujeitos da plateia sobre temáticas da atualidade e/ou relativas à vida dos convidados. Ambos os programas compartilham das mesmas convenções a partir das quais o gênero é estruturado - os atores sociais e os recursos semióticos -, porém as diferenças observadas decorrem dos valores sociais específicos nos quais os objetivos de cada um estão ancorados. Compreendemos, assim, que a inovação que Manos e Minas exibe em relação a outros exemplares do gênero programa de auditório é o compromisso com a formação de uma consciência de classe. Em função disso, a estrutura de produção do programa é voltada aos interesses e às temáticas das periferias brasileiras e apresenta uma vinculação não apenas com o entretenimento, mas fundamentalmente com a arte, a cultura e a política. Já em relação ao Altas Horas, esse é um exemplar do gênero programa de auditório que compartilha com outros programas o mesmo objetivo: o entretenimento a partir de valores sociais da grande mídia. Com relação aos elementos estruturadores do gênero programa de auditório, este deriva sua organização temática da inter-relação entre (i) sistema de valores sociais, vinculados a grupos sociais específicos; (ii) convenções linguísticas relativas às práticas de referenciação e à escolha de um conjunto de tópicos; (iii) o mundo representado na televisão por atores sociais legítimos representantes desse mundo e, ainda, (iv) a manipulação de recursos multisemióticos / Abstract: This research aims to understand the aspects of innovation, manipulation and change of the auditorium TV show genre. For this, the analyses dedicate to describe and to compare two auditorium TV shows: Manos e Minas and Altas Horas. We intend to know which the aspects of innovation, manipulation and change of this genre are and how stability and innovation are linked in order to contribute to a better understanding of the relatively stable nature of discourse genres. Based on the articulation between the theories about discourse genres and theories about multimodal genres, we favor the description and analysis of the general auditorium TV show structure and themes privileged by each one. Manos e Minas aims to bring 'the voice of the periphery' to the television media for the recovery of the practices of this community and Altas Horas to interview public figures and to interact with the local audience on topics of current and / or concerning to the life of its guests. Both TV shows share the same conventions which the genre is structured on - the social actors and the semiotic resources -, but the differences arise from the specific social values which the goals of each one are anchored in. We understand, therefore, that the innovation displayed by Manos e Minas in relation to other examples of auditorium TV show genre is the commitment to the formation of a class consciousness. As a result, the structure of the production of this TV Show is focused on the interests and issues of Brazilian peripheries, presenting a link, not only with entertainment, but mostly with art, culture and politics. Regarding to Altas Horas, this is an exemplar of the auditorium TV show genre which shares with other TV shows the same goal: the entertainment based on social values of the large media. In relation to structural elements of the auditorium TV show genre, it derives its thematic organization from the interrelationship among (i) social value system, linked to specific social groups; (ii) linguistic conventions concerning to the referencing practices and to the choice of a range of topics; (iii) the world as depicted on the television by social actors legitimate representatives of this world and also (iv) the manipulation of multisemiotics resources / Mestrado / Linguistica / Mestre em Linguística

The subject of this diploma thesis is the potential of organizations of civil society to influence public debate about immigration to Europe via Facebook. Conclusions introduced in this diploma thesis are based on my own empirical research as well as on literature focused on public relations. Research is designed as single case study of Facebook communication of Doctors without Borders. I explore the diversity of topics and argumentation present in the organization's communication, reactions of its audience and mutual interactions between organization and its audience. I explain that content, visual and formal aspects may play a key role when an organization is trying to address wide audience, whose ideas is willing to shape and influence. Research points out that the communication of Doctors without Borders about migration to Europe is one-sided, because it's mainly driven by activities and mission of the organization. This one-sidedness is partly compensated by engaged audience that enriches discussions under the Facebook posts of the organization with diverse topics and opinions. The thesis tries to capture the significance of tension between organization and its audience that raises inspirational discussions, which might not occur in case of absolute consensus. Key words communication, public...

Despite the accessibility of online news and availability of sophisticated methods for analyzing news content, no previous study has focused on the simultaneous examination of news coverage on human trafficking and audiences' interpretations of this coverage. In my research, I have examined both journalists' and commenters' topic choices in coverage and discussion of human trafficking from the online platforms of three British newspapers covering the period 2009–2015. I used latent semantic analysis (LSA) to identify emergent topics in my corpus of newspaper articles and readers' comments, and I then quantitatively investigated topic preferences to identify convergence and divergence on the topics discussed by journalists and their readers. I addressed my research questions in two distinctive studies. The first case study implemented topic modelling techniques and further quantitative analyses on article and comment paragraphs from The Guardian. The second extensive study included article and comment paragraphs from the online platforms of three British newspapers: The Guardian, The Times and the Daily Mail. The findings indicate that the theories of "agenda setting" and of "active audience" are not mutually exclusive, and the scope of explanation of each depends partly on the specific topic or subtopic that is analyzed. Taking into account further theoretical concepts related to agenda setting, four more additional research questions were addressed. Topic convergence and divergence was further identified when taking into account the newspapers' political orientation and the articles' and comments' year of publication.

We used tweets to collect public discussion on organizations' activities during the specified Covid19 period. Through topic modeling, we were able to establish discussed topics in line with the organization's activities. Our research majored on tweets with matching hashtags W.H.O (world health organization) and coronavirus, covid19 or covid. We extracted five latent topics and explored the distribution or evolution of those topics over time. We were able to find people's opinions on hot topics (the period when a topic is mainly discussed); the hot topics reflect activities on the timeline of W.H.O during the specified period of the Pandemic. Our results show that the key topics are identified and characterized by specific events that happened during the specified period in our data. Our result describes the events that happened on the timeline of the W.H.O, showing the public opinion on each period a discussion is hot. It also shows how people's opinions revolve during the period. Our results will be helpful in identifying public sentiment on events, how people's opinion varies, and can also help understand different events of the organization based on the aim and objective of the event.

The nurse practitioner (NP) role is more prominent now than ever before in primary healthcare, positioning them as providers who defend initiatives and ongoing health agendas. Obesity is among those agendas. The concept of instrumental role modeling was explained as a combination of understanding and physical presence that gives meaning and quality to inspire change. It implied that health professionals are not merely insightful clinicians but suggested their expertise is complimented by demonstrations of wellness in knowledge and practice. This topic of weight was perceived as sensitive but must be addressed. In this grounded theory study, the perspectives of NPs from clinical and academic settings were gathered. There was an overarching need for NPs to identify how they perceived themselves consequential to how others perceived them. Using a qualitative method gaps on the construct of instrumental role modeling as an emerging theory was addressed and revealed the ambiguities NPs encountered when challenged to identify their personal perceptions of obesity when counseling weight management. Using a grounded theory design, 11 NPs were interviewed and asked about how they reconciled perceptions of instrumental role modeling around discussions of obesity. Participant remarks produced theoretical constructs that instrumental role models: 1) are mindfully responsible when interacting with others, 2) need to balance accountability, approach and awareness to develop trust, and 3) need to be aware of the creative tensions that exist between accountability and approach when discussing illnesses and their co-morbid conditions. These findings provide evaluative dialogue for positive social change in clinical settings and valuable insight regarding the topic of obesity in academia.

This paper aims to show how User Generated Content can create value for Smart Tourism Destinations. Applying the analysis on 5 different cases in the region of Stockholm to derive patterns and opportunities of value creation generated by UGC in tourism. Findings of this paper is also discussed in terms of improving decision making, possibilities of new business models and importance of technological improvements on STD’s. Finally, thoughts on models are presented for researchers and practitioners that might be interested in exploitation of UGC in the context of information-intensive industries and mainly in Tourism.

Adverse drug reactions are unwanted effects alongside the intended benefit of a drug and might be responsible for 3-7\% of hospitalizations. Finding such reactions is partly done by analysing individual case safety reports (ICSR) of adverse events. The reports consist of categorical terms that describe the event.Data-driven identification of suspected adverse drug reactions using this data typically considers single adverse event terms, one at a time. This single term approach narrows the identification of reports and information in the reports is ignored during the search. If one instead assumes that each report is connected to a topic, then by creating a cluster of the reports that are connected to the topic more reports would be identified. More context would also be provided by virtue of the topics. This thesis takes place at Uppsala Monitoring Centre which has implemented a probabilistic model of how an ICSR, and its topic, is assumed to be generated. The parameters of the model are estimated with expectation maximization (EM), which also assigns the reports to clusters. The clusters are improved with Consensus Clustering that identify groups of reports that tend to be grouped together by several runs of EM. Additionally, in order to not cluster outlying reports all clusters below a certain size are excluded. The objective of the thesis is to improve the algorithm in terms of computational efficiency and quality, as measured by stability and clinical coherence. The convergence of EM is improved using stepwise EM, which resulted in a speed up of at least 1.4, and a decrease of the computational complexity. With all the speed improvements the speed up factor of the entire algorithm can reach 2 but is constrained by the size of the data. In order to improve the clusters' quality, the community detection algorithm Leiden is used. It is able to improve the stability with the added benefit of increasing the number of clustered reports. The clinical coherence score performs worse with Leiden. There are good reasons to further investigate the benefits of Leiden as there were suggestions that community detection identified clusters with greater resolution that still appeared clinically coherent in a posthoc analysis.