Altmetrics is a new bibliometric subfield that uses data from online platforms and social and mainstream media to track attention to and impact of scholarly content. Qualitative research is needed to increase knowledge of altmetrics and of what they may indicate about scholarly publications’ impact and influence. Through analyzing the second-largest source of altmetric events, tweets to academic articles, this thesis extends our understanding of these metrics. Using content analysis and an adapted framework for categorizing acts by levels of engagement, I analyzed 1,200 tweets to four humanities articles, recording their engagement with the articles, sentiment, hashtag use, and @mentions. I also categorized 203 of the tweeting accounts. There is considerable inter-article variation among tweets to the four articles. Overall, however, the tweets evidence low engagement with the articles, the retweet percentage is high, and many of the tweets are traced to few accounts. Contradicting prior suggestions that tweets may be particularly suited to indicating public engagement with scholarly articles, a large proportion of the tweets appear to be from academics. Confirming findings of prior studies, the results indicate that academics use Twitter to filter scholarly literature. I conclude that a single altmetric score is too reductive and of negligible use without deeper qualitative analysis. Unlike some altmetrics indicators that may reveal impact, tweets to articles rather indicate attention, casting doubt on the claim that altmetrics as a whole measure impact. Despite these limitations, tweets to articles and altmetrics more broadly can provide meaningful information not conveyed by citations.

Scholarly impact and visibility have traditionally been assessed by estimating the number and quality of publications and citations in the scholarly literature. But now scholars are increasingly visible on the Web. Twitter, Mendeley and other social media platforms are quite well-known and interesting tools for sharing research articles among scholars. Based on the capabilities of altmetrics, this thesis analyses the altmetric coverage and impact of LIS articles published by Swedish universities during 2013 to 2017. It also tries to paint a picture of demographic of people engaged with these articles. The most common altmetric sources are considered using a sample of 170 LIS journal articles. The findings were interpreted using two different sociological theories: the normative theory of Merton´s norms and the theory of social constructivism. The result of the study showed that Mendeley has the highest coverage of journal articles (65 percent) followed by Twitter (33 percent) while very few of the publications are mentioned in blogs or on Facebook. Researchers were the main Mendeley readers of articles with 53 percent, followed by the general public at 26 percent. This study, on the other hand, found out that public users were the main group that shared articles on Twitter. The list of articles with a high number of tweets showed that most topics in the field of LIS are associated with bibliometrics and citation impacts. The results demonstrate that the adoption of altmetric methods within the LIS fields is inevitable, but several issues must be considered to identify their potential.

Lowery will provide an overview of altmetrics with a focus on the most recent developments within the field. Topics will include types of altmetrics, tools used to track altmetrics, and applications of altmetrics.

Submitted by Alison Vanceto (alison-vanceto@hotmail.com) on 2017-02-17T12:05:18Z No. of bitstreams: 1 DissPRC.pdf: 3774120 bytes, checksum: ac43c623fcb4cf2efe4eaf196a15389d (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-03-09T18:40:12Z (GMT) No. of bitstreams: 1 DissPRC.pdf: 3774120 bytes, checksum: ac43c623fcb4cf2efe4eaf196a15389d (MD5) / Approved for entry into archive by Ronildo Prado (ronisp@ufscar.br) on 2017-03-09T18:40:30Z (GMT) No. of bitstreams: 1 DissPRC.pdf: 3774120 bytes, checksum: ac43c623fcb4cf2efe4eaf196a15389d (MD5) / Made available in DSpace on 2017-03-09T18:51:50Z (GMT). No. of bitstreams: 1 DissPRC.pdf: 3774120 bytes, checksum: ac43c623fcb4cf2efe4eaf196a15389d (MD5) Previous issue date: 2017-01-16 / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / The existence of innumerous barriers to access scientific knowledge gave rise to the movement in favor of open access. The impact of scientific research tends to be measured by the total number of citations the work gets, and so the hypothesis of a possible Open Access Citation Advantage (OACA) emerged, in which it is argued that the articles available in open access have an advantage in the number of citations in relation to those only available in restricted publications. However, assessing the impact of a scientific publication must go beyond the analysis of citations, as it is necessary to consider that scientists do not cite all references that may have influenced them during the research, and that other actors are also part of the scientific community. For these reasons, the use of alternative metrics to assist the evaluation of science has been discussed in a new subfield called Altmetrics. In this sense, the aim of this study was to investigate the potential benefits that open access can offer to the field of Information Science. Therefore, bibliometric citation indicators and altmetric indicators for four journals were collected and analyzed: Journal of the American Society for Information Science, Scientometrics, El Profesional de la Información and Transinformação. Data sources covered Web of Science, Google Scholar, Altmetric.com and Mendeley. The results indicated that open access actually offered advantages over the average number of citations and references in the social web received in all hybrid journals. This fact confirms the validity of the OACA hypothesis for the Information Science area. It was also found that this advantage is maintained, at least, until the eighth year after publication, and it extends to the altmetrics data. / A existência de diversas barreiras de acesso ao conhecimento científico levaram a um movimento em prol do acesso aberto. Como o impacto de uma pesquisa científica costuma ser ponderado pelo número total de citações que o trabalho recebe, surgiu a hipótese do Open Access Citation Advantage (OACA), na qual argumenta-se que os artigos disponibilizados em acesso aberto possuem uma vantagem no número de citações em relação às publicações de acesso restrito. No entanto, avaliar o impacto de uma publicação científica deve ir além da análise de citações, pois é necessário considerar que os cientistas não citam todas as referências que os influenciaram durante a pesquisa e que outros atores também fazem parte da comunidade científica. Por essas razões, a utilização de métricas alternativas que auxiliem a avaliação da ciência vem sendo discutidas em um novo subcampo do conhecimento, chamado Altmetria. Neste sentido, o objetivo deste estudo foi investigar as possíveis vantagens que o acesso aberto pode oferecer ao campo da Ciência da Informação. Para tanto, foram elaborados e analisados indicadores bibliométricos de citação e indicadores altmétricos para quatro periódicos científicos: Journal of the American Society for Information Science, Scientometrics, El Profesional de la Información e Transinformação. As fontes de dados abrangeram a Web of Science, o Google Acadêmico, a Altmetric.com e o Mendeley. Os resultados indicaram que o acesso aberto realmente oferece vantagens em relação ao número médio de citações e de menções na web social recebidas em todas as revistas híbridas, fato que confirma a validade da hipótese de OACA para a área da Ciência da Informação. Verificou-se ainda que essa vantagem se mantém, pelo menos até o oitavo ano após a publicação, e que ela também se estende para os dados altmétricos. / FAPESP: 2015/16872-2

The purpose of the thesis is i) to discover the latent topics of SDG13 and their coverage in news media ii) to investigate the share of OA and Non-OA articles and reviews in each topic iii) to compare the share of different OA types (Green, Gold, Hybrid and Bronze) in each topic. It imposes a heuristic perspective and explorative approach in reviewing the three concepts open access, altmetrics and climate action (SDG13). Data is collected from SciVal, Unpaywall, Altmetric.com and Scopus rendering a dataset of 70,206 articles and reviews published between 2014-2018. The documents retrieved are analyzed with descriptive statistics and topic modeling using Sklearn’s package for LDA(Latent Dirichlet Allocation) in Python. The findings show an altmetric advantage for OA in the case of news media and SDG13 which fluctuates over topics. News media is shown to focus on subjects with “visible” effects in concordance with previous research on media coverage. Examples of this were topics concerning emissions of greenhouse gases and melting glaciers. Gold OA is the most common type being mentioned in news outlets. It also generates the highest number of news mentions while the average sum of news mentions was highest for documents published as Bronze. Moreover, the thesis is largely driven by methods used and most notably the programming language Python. As such it outlines future paths for research into the three concepts reviewed as well as methods used for topic modeling and programming.

Submitted by Josimara Dias Brumatti (bcgdigital@ndc.uff.br) on 2017-01-26T13:03:43Z No. of bitstreams: 1 2014_Mest_PPGCI-UFF_IaraVidal.pdf: 1139977 bytes, checksum: c060d1dc8e124903f244f016f7b0fa45 (MD5) / Approved for entry into archive by Geisa Drumond (gmdrumond@vm.uff.br) on 2017-01-27T15:05:23Z (GMT) No. of bitstreams: 1 2014_Mest_PPGCI-UFF_IaraVidal.pdf: 1139977 bytes, checksum: c060d1dc8e124903f244f016f7b0fa45 (MD5) / Made available in DSpace on 2017-01-27T15:05:23Z (GMT). No. of bitstreams: 1 2014_Mest_PPGCI-UFF_IaraVidal.pdf: 1139977 bytes, checksum: c060d1dc8e124903f244f016f7b0fa45 (MD5) / A proposta deste trabalho é traçar o estado da arte da altmetria, definida como o estudo, a criação e a utilização de indicadores relacionados à interação de usuários com produtos de pesquisa diversos no âmbito da Web Social – visualizações, downloads, citações, reutilizações, compartilhamentos, etiquetagens, comentários, entre outros. Para entender o contexto de surgimento da altmetria, exploramos as especificidades e potencialidades da Web Social e as características da comunicação científica. Além de constituir mais um passo na evolução dos estudos métricos da informação, a altmetria se apresenta também como reação à crise do atual modelo de publicação e avaliação na Ciência. A partir de pesquisa bibliográfica exploratória em fontes nacionais e internacionais, levantamos a produção científica sobre altmetria, identificando atores envolvidos na produção de conhecimento na área, seus conceitos, as propostas e tendências dos estudos sobre o tema; fundamentando a reflexão sobre o desenvolvimento da área e a aceitação das métricas alternativas como ferramentas da avaliação científica. Constatamos que a altmetria é uma área de estudos em expansão, cujos métodos complementam os estudos métricos tradicionais contribuindo para o entendimento mais completo da comunicação científica, seus atores, seus processos, seus produtos e seus impactos. / Describes the state of the art of altmetrics, defined as the study, creation and use of measures related to user interaction with diverse research products through the Social Web – views, downloads, citations, reuse, sharing, tagging, comments, among others. To understand the context where altmetrics arises, we explore the Social Web’s specificities and potentials, and the characteristics of scientific communication. Besides being another step on the evolution of metric studies of information, altmetrics also presents itself as a reaction to the crisis in the current model of scientific publication and evaluation. Through an exploratory search in national and international sources we were able to identify the scientific literature about altmetrics, analysing the authors involved, its concepts, the proposals and trends around the theme, basing our reflection about the development of altmetrics and the acceptance of alternative metrics as tools for scientific evaluation. We note that altmetrics is an expanding area, and its methods complement traditional metrics contributing to a more complete understanding of scientific communication, its actors, processes, products and impacts.

Combating crime is a complex task with cultural, political, and legal dimensions. In technologically advanced societies, surveillance technology can be used to aid law enforcement. A few examples of such tools are drones, cameras, and wiretaps to mention a few. As such tools become more commonplace, the need to address associated issues increase which relate to cultural, political, and legal dimensions and different stakeholders. Hence, the purpose of this thesis is to discern the impact of informatics research on surveillance technology and map out similarities and discrepancies between views of social media users, researchers, and professionals within law enforcement. The thesis impose a heuristic perspective and stem from both positivist and interpretivist tradition. The Panopticon metaphor and Panopticism are used as a theoretical lens, mainly to discuss and contextualize the findings. Data was from Twitter and Scopus by using scripts and by conducting an interview with law enforcement staff in Sweden. A total of 88 989 tweets and 4 874 research papers were retrieved. These were analyzed using topic modeling which assigned a dominant topic to each tweet and research paper. The interview was thematized using both the literature review and the topic modeling findings for guiding framework. The findings showed that there were seven topics found within the Scopus dataset and four topics within the Twitter dataset. It was found that privacy was one of the least mentioned aspects in all three datasets and that law enforcement personnel see it as closely related with efficiency. Military applications and usage were found in both research papers and tweets and law enforcement staff use a variety of ICT in their daily work. Based on the findings, it seems as though surveillance technology today can suitably be characterized as being bi-directional, both in the form of sousveillance and surveillance which relates to the Deleuzian perspectives on Panopticon. It was concluded that concrete implementations of surveillance technology attracted the most attention compared to more abstract themes such as ethics and privacy. But in all both datasets, specific ICT was addressed from a critical perspective. Similarly, law enforcement personnel viewed privacy and integrity from the organization’s perspective and highlighted rules and regulation. For future work, sentiment analysis is suggested to supplement topic modeling as well as imposing a longitudinal approach or adding additional social media sources.

[EN] The object of this study is the design of a cybermetric methodology whose objectives are to measure the success of the content published in an online media and the possible prediction of the selected success variables. Framed in the field of digital journalism, it responds to the need to analyze the success of web content so that it can help in the decision-making of the editorial team of a digital medium. A line of research focused on the content itself, providing an innovative vision to that of previous research, and a methodology that serves as a basis for future scientific advances. It is about the contribution of valuable information, either from the statistical analysis of the data or from the possible prediction of the success indicators of greatest interest to the environment. In this way, it could be integrated as a feedback into the content strategy and thus favor its iterative optimization. The main objective, therefore, is the design of a cybermetric methodology for calculating the success of an online publication, having as specific objectives: to research the concept of success in digital journalism, the social network Twitter, web analytics and web advertising; design the methodology and determine what tools and reports are needed; extract and process data for statistical analysis; perform regressions that allow to obtain prediction equations of the selected success variables; and validate the prediction equations with test data and obtain their precision, serving this as a degree of confidence in the prediction. The design of the methodology has served to observe a significant over-dispersion in the data, as well as to demonstrate that the success of a web content has a strongly multifactorial nature, which causes a decrease in the variability calculated using the indicators proposed by previous research. This thesis serves, then, as the basis for a very interesting research framework both at an academic and business level: the prediction of the success of digital content. / [ES] El objetivo de estudio es el diseño de una metodología cibermétrica para medir el éxito de los contenidos publicados en un medio de comunicación online y su posible predicción, de manera que se pueda orientar la optimización de los futuros contenidos publicados por el medio. Enmarcada en el ámbito del periodismo digital, responde a la necesidad de analizar el éxito de los contenidos web de manera que se pueda ayudar en la toma de decisiones del equipo editorial. Para ello, se ha realizado un extenso estudio de las publicaciones académicas versadas en las diferentes disciplinas que tienen lugar en esta tesis: la comunicación de contenidos digitales, Twitter, la difusión de las noticias en Twitter, la analítica web, la cibermetría, la analítica en Twitter, el análisis de tendencias en Twitter y la publicidad web. Con dicho marco, se ha obtenido información valiosa para la optimización futura de los contenidos digitales, ya sea procedente del análisis estadístico de los datos o de la posible predicción de los indicadores de éxito de mayor interés para el medio. De esta manera, se podría integrar de manera retroalimentada en la estrategia de contenidos y favorecer así su optimización iterativamente. Para ello, se han tenido en cuenta los siguientes objetivos específicos: investigar el concepto de éxito en el periodismo digital, la red social Twitter, la analítica web y la publicidad en la web; diseñar la metodología y determinar qué herramientas y reportes son necesarios; extraer y procesar los datos para su análisis estadístico; realizar regresiones que permitan obtener ecuaciones de predicción de las variables de éxito seleccionadas; y validar las ecuaciones de predicción con datos de test y obtener su precisión, sirviendo esta como grado de confianza en la predicción. El diseño de la metodología ha servido para observar una sobre dispersión significativa en los datos, así como demostrar que el éxito de un contenido web tiene un carácter fuertemente multifactorial, lo cual provoca una disminución en la variabilidad calculada mediante los indicadores propuestos por investigaciones previas. Esta tesis sirve, entonces, como base para una línea de investigación sobre la optimización de contenido digital basándose en la predicción estadística de su éxito. / [CAT] L'objectiu d'estudi és el disseny d'una metodologia cibermètrica per a mesurar l'èxit dels continguts publicats en un mitjà de comunicació en línia i la seua possible predicció, de manera que es puga orientar l'optimització dels futurs continguts publicats pel mitjà. Emmarcada en l'àmbit del periodisme digital, respon a la necessitat d'analitzar l'èxit dels continguts web de manera que es puga ajudar en la presa de decisions de l'equip editorial. Per a això, s'ha realitzat un extens estudi de les publicacions acadèmiques versades en les diferents disciplines que tenen lloc en aquesta tesi: la comunicació de continguts digitals, Twitter, la difusió de les notícies en Twitter, l'analítica web, la cibermetría, l'analítica en Twitter, l'anàlisi de tendències en Twitter i la publicitat web. Amb aquest marc, s'ha obtingut informació valuosa per a l'optimització futura dels continguts digitals, ja siga procedent de l'anàlisi estadística de les dades o de la possible predicció dels indicadors d'èxit de major interés per al mitjà. D'aquesta manera, es podria integrar de manera retroalimentada en l'estratègia de continguts i afavorir així la seua optimització iterativament. Per a això, s'han tingut en compte els següents objectius específics: investigar el concepte d'èxit en el periodisme digital, la xarxa social Twitter, l'analítica web i la publicitat en la web; dissenyar la metodologia i determinar quines eines i reportes són necessaris; extraure i processar les dades per a la seua anàlisi estadística; realitzar regressions que permeten obtindre equacions de predicció de les variables d'èxit seleccionades; i validar les equacions de predicció amb dades de test i obtindre la seua precisió, servint aquesta com a grau de confiança en la predicció. El disseny de la metodologia ha servit per a observar una sobre dispersió significativa en les dades, així com demostrar que l'èxit d'un contingut web té un caràcter fortament multifactorial, la qual cosa provoca una disminució en la variabilitat calculada mitjançant els indicadors proposats per investigacions prèvies. Aquesta tesi serveix, llavors, com a base per a una línia d'investigació sobre l'optimització de contingut digital basant-se en la predicció estadística del seu èxit. / Yeste Moreno, VM. (2021). Diseño de una metodología cibermétrica de cálculo del éxito para la optimización de contenidos web [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/176009