Web citations in patents: Evidence of technological impact?

This is an accepted manuscript of an article published by Wiley Blackwell in Journal of the Association for Information Science and Technology on 17/07/2017, available online: https://doi.org/10.1002/asi.23821 The accepted version of the publication may differ from the final published version.Patents sometimes cite web pages either as general background to the problem being addressed or to identify prior publications that will limit the scope of the patent granted. Counts of the number of patents citing an organisation’s website may therefore provide an indicator of its technological capacity or relevance. This article introduces methods to extract URL citations from patents and evaluates the usefulness of counts of patent web citations as a technology indicator. An analysis of patents citing 200 US universities or 177 UK universities found computer science and engineering departments to be frequently cited, as well as research-related web pages, such as Wikipedia, YouTube or Internet Archive. Overall, however, patent URL citations seem to be frequent enough to be useful for ranking major US and the top few UK universities if popular hosted subdomains are filtered out, but the hit count estimates on the first search engine results page should not be relied upon for accuracy

Identifying institutional relationships in a geographically distributed public health system using interlinking and co-authorship methods

The final publication is available at Springer via http://dx.doi.org/ 10.1007/s11192-016-1839-zLink analysis is highly effective in detecting relationships between different institutions, relationships that are stronger the greater their geographical proximity. We therefore decided to apply an interlinking analysis to a set of geographically dispersed research entities and to compare the results with the co-authorship patterns between these institutions in order to determine how, and if, these two techniques might reveal complementary insights. We set out to study the specific sector of public health in Spain, a country with a high degree of regional autonomy. We recorded all Spanish health entities (and their corresponding URLs) that belong to, and were hyperlinked from, the national government or any of the regional governments, gathering a total of 263 URLs. After considering their suitability for web metric analysis, interlinking scores between all valid URLs were obtained. In addition, the number of co-authored articles by each pair of institutions and the total scientific output per institution were retrieved from Scopus. Both interlinking and co-authorship methods detect the existence of strength subnets of geographically distributed nodes (especially the Catalan entities) as well as their high connectivity with the main national network nodes (subnet of nodes distributed according to dependence on national government, in this case Spain). However, the resulting interlinking pattern shows a low but significant correlation (r = 0.5) with scientific co-authorship patterns. The existence of institutions that are strongly interlinked but with limited scientific collaboration (and vice versa) reveals that links within this network are not accurately reflecting existing scientific collaborations, due to inconsistent web content development.Ontalba Ruipérez, JA.; Orduña Malea, E.; Alonso-Arroyo, A. (2016). Identifying institutional relationships in a geographically distributed public health system using interlinking and co-authorship methods. Scientometrics. 106(3):1167-1191. doi:10.1007/s11192-016-1839-zS116711911063Aguillo, I. F., Granadino, B., Ortega, J. L., & Prieto, J. A. (2006). Scientific research activity and communication measured with cybermetrics indicators. Journal of the American Society for Information Science and Technology, 57(10), 1296–1302.Almind, T. C., & Ingwersen, P. (1998). Informetric analyses on the world wide web: methodological approaches to ‘webometrics’. Journal of Documentation, 53(4), 404–426.Barabasi, A. L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509–512.Bar-Ilan, J. (2005). What do we know about links and linking? A framework for studying links in academic environments. Information Processing and Management, 41(4), 973–986.Barnett, George A., & Park, Han W. (2014). 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Scientometrics, 58(2), 391–413.Heimeriks, G., & Van den Besselaar, P. (2006). Analyzing hyperlinks networks: The meaning of hyperlink based indicators of knowledge production. Cybermetrics, 10(1), http://cybermetrics.cindoc.csic.es/articles/v10i1p1.pdf . Accessed 16 August 2015.Holmberg, K. (2010). Co-inlinking to a municipal Web space: A webometric and content analysis. Scientometrics, 83(3), 851–862.Holmberg, K., & Thelwall, M. (2009). Local government web sites in Finland: A geographic and webometric analysis. Scientometrics, 79(1), 157–169.Khan, G. F., & Park, H. W. (2011). Measuring the triple helix on the web: Longitudinal trends in the university-industry-government relationship in Korea. Journal of the American Society for Information Science and Technology, 62(12), 2443–2455.Lang, P. B., Gouveia, F. C., & Leta, J. (2014). Health research networks on the web: An analysis of the Brazilian presence. Cadernos de Saúde Pública, 30(2), 369–378.Leydesdorff, L., & Curran, M. (2000). 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Aslib Proceedings, 66(1), 96–116.Orduna-Malea, E., & Aguillo, I. F. (2014). Cibermetría. Midiendo el espacio red. Barcelona: UOC Publishing.Orduna-Malea, E., & Aytac, S. (2015). Revealing the online network between university and industry: The case of Turkey. Scientometrics, 105(3), 1849–1866.Orduna-Malea, E., Delgado López-Cózar, E., Serrano-Cobos, J., & Romero, N. L. (2015a). Disclosing the network structure of private companies on the web: The case of Spanish IBEX 35 share index. Online Information Review, 39(3), 360–382.Orduna-Malea, E., & Ontalba-Ruipérez, J. A. (2013). Proposal for a multilevel university cybermetric analysis model. Scientometrics, 95(3), 863–884.Orduna-Malea, E., Torres-Salinas, D., & Delgado López-Cózar, E. (2015b). Hyperlinks embedded in twitter as a proxy for total external in-links to international university websites. Journal of the Association for Information Science and Technology, 66(7), 1447–1462.Ortega, J. L. (2007). Visualización de la Web universitaria Europea: análisis cuantitativo de enlaces a través de técnicas cibermétricas. Madrid: Universidad Carlos III de Madrid.Ortega, J. L., & Aguillo, I. F. (2009). Mapping world-class universities on the web. Information Processing and Management, 45(2), 272–279.Ortega, J. L., Orduna-Malea, E., & Aguillo, I. F. (2014). Are web mentions accurate substitutes for inlinks for Spanish universities? Online Information Review, 38(1), 59–77.Park, H. W. (2011). How do social scientists use link data from search engines to understand Internet-based political and electoral communication? Quality and Quantity, 46(2), 679–693.Park, H. W., & Thelwall, M. (2003). Hyperlink analyses of the World Wide Web: A review. Journal of Computer-Mediated Communication. doi: 10.1111/j.1083-6101.2003.tb00223.x .Romero-Frías, E., & Vaughan, L. (2010a). Patterns of web linking to heterogeneous groups of companies: The case of stock exchange indexes. Aslib Proceedings, 62(2), 144–164.Romero-Frías, E., & Vaughan, L. (2010b). European political trends viewed through patterns of Web linking. Journal of the American Society for Information Science and Technology, 61(10), 2109–2121.Seeber, M., Lepori, B., Lomi, A., Aguillo, I. F., & Barberio, V. (2012). Factors affecting web links between European higher education institutions. Journal of Informetrics, 6(3), 435–447.Stuart, D., & Thelwall, M. (2006). Investigating triple helix relationships using URL citations: A case study of the UK West Midlands automobile industry. Research Evaluation, 15(2), 97–106.Sud, P., & Thelwall, M. (2014). Linked title mentions: A new automated link search candidate. Scientometrics, 101(3), 1831–1849.Thelwall, M. (2001). Extracting macroscopic information from web links. Journal of the American Society for Information Science and Technology, 52(13), 1157–1168.Thelwall, M. (2002). Evidence for the existence of geographic trends in university web site interlinking. Journal of Documentation, 58(5), 563–574.Thelwall, M. (2004). Link analysis: An information science approach. San Diego: Elsevier.Thelwall, M. (2006). Interpreting social science link analysis research: A theoretical framework. Journal of the American Society for Information Science and Technology, 57(1), 60–68.Thelwall, M. (2009). Introduction to webometrics: Quantitative web research for the social sciences. San Rafael, CA: Morgan & Claypool Publishers.Thelwall, M., & Sud, P. (2011). A comparison of methods for collecting web citation data for academic organisations. Journal of the American Society for Information Science and Technology, 62(8), 1488–1497.Thelwall, M., & Tang, R. (2003). Disciplinary and linguistic considerations for academic web linking: An exploratory hyperlink mediated study with Mainland China and Taiwan. Scientometrics, 58(1), 155–181.Thelwall, M., Tang, R., & Price, L. (2003). Linguistic patterns of Academic web use in Western Europe. Scientometrics, 56(3), 417–432.Vaughan, L. (2006). Visualizing linguistic and cultural differences using web co-link data. Journal of the American Society for Information Science and Technology, 57(9), 1178–1193.Vaughan, L., & Thelwall, M. (2003). Scholarly use of the web: What are the key inducers of links to journal web sites? Journal of the American Society for Information Science and Technology, 54(1), 29–38.Vaughan, L., & Thelwall, M. (2004). Search engine coverage bias: Evidence and possible causes. Information Processing and Management, 40(4), 693–707.Vaughan, L., & Wu, G. (2004). Links to commercial websites as a source of business information. Scientometrics, 60(3), 487–496.Vaughan, L., & You, J. (2006). Comparing business competition positions based on Web co-link data: The global market vs. the Chinese market. Scientometrics, 68(3), 611–628.Weber, M. S., & Monge, P. (2011). 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Redes de conectividad entre empresas tecnológicas a través de un análisis métrico longitudinal de menciones de usuario en Twitter

El objetivo principal de este trabajo es identificar y describir (mediante un análisis cibermétrico de menciones de usuario) la intensidad y evolución de las relaciones establecidas entre compañías de un determinado sector industrial (tecnología) a través de sus correspondientes cuentas corporativas de Twitter, con el propósito de comprobar el valor que un análisis métrico de estas características puede tener a la hora de determinar la conectividad entre dichas compañías. Para ello se han contabilizado las menciones, tanto directas (MT) como ReTweets (RT), entre las cuentas de Twitter de una muestra de 50 compañías internacionales durante un período de seis meses. Los resultados indican que el grado de interacción entre las 50 empresas tecnológicas es débil (tanto si contamos el número de conexiones establecidas como si cuantificamos la intensidad de estas conexiones), estable, concentrado en unas pocas relaciones específicas y de carácter marcadamente asimétrico. Se concluye que, dada la baja interactividad detectada, las cuentas corporativas de las empresas tecnológicas en Twitter no son suficientes para analizar desde un punto de vista métrico la conectividad web establecida entre éstas, aunque sí útiles para conocer las políticas de comunicación oficiales entre ellas.This work has been carried out in the framework of the research project with reference APOSTD/2013/002, funded by the Regional Ministry of Education, Culture and Sport (Generalitat Valenciana, Spain).Azorín-Richarte, D.; Orduña Malea, E.; Ontalba Ruipérez, JA. (2016). Redes de conectividad entre empresas tecnológicas a través de un análisis métrico longitudinal de menciones de usuario en Twitter. Revista española de Documentación Científica. 39(3):1-20. https://doi.org/10.3989/redc.2016.3.1316S120393Adamic, L. A., & Huberman, B. A. (2001). The Web’s hidden order. Communications of the ACM, 44(9), 55-60. doi:10.1145/383694.383707Barabási, A.L. (2014). Linked: how everything is connected to everything else and what it means for business, Science, and every day life. New York: Basic Books.Barabási, A.-L., & Albert, R. (1999). Emergence of Scaling in Random Networks. Science, 286(5439), 509-512. doi:10.1126/science.286.5439.509Bollen, J., Mao, H., & Zeng, X. (2011). Twitter mood predicts the stock market. Journal of Computational Science, 2(1), 1-8. doi:10.1016/j.jocs.2010.12.007Carim, L., & Warwick, C. (2013). Use of social media for corporate communications by research-funding organisations in the UK. Public Relations Review, 39(5), 521-525. doi:10.1016/j.pubrev.2013.08.006Case, C. J.; King, D. L. (2010). Cutting edge communication: microblogging at the fortune 200, twitter implementation and usage. Issues in information systems, vol. 11(1), 216-223.Del-Fresno-García, M. (2014). Haciendo visible lo invisible: visualización de la estructura de las relaciones en red en Twitter por medio del análisis de redes sociales. El Profesional de la Informacion, 23(3), 246-252. doi:10.3145/epi.2014.may.04Gentle, A. (2009). Conversation and community: the social web for documentation. Laguna Hills; XML Press, p. 342.Huberman, B., Romero, D. M., & Wu, F. (2008). Social networks that matter: Twitter under the microscope. First Monday, 14(1). doi:10.5210/fm.v14i1.2317Jansen, B. J., Zhang, M., Sobel, K., & Chowdury, A. (2009). Twitter power: Tweets as electronic word of mouth. Journal of the American Society for Information Science and Technology, 60(11), 2169-2188. doi:10.1002/asi.21149Kietzmann, J. H., Hermkens, K., McCarthy, I. P., & Silvestre, B. S. (2011). Social media? Get serious! Understanding the functional building blocks of social media. Business Horizons, 54(3), 241-251. doi:10.1016/j.bushor.2011.01.005Ordu-a-Malea, E.; Aguillo, I.F. (2014). Cibermetría: midiendo el espacio red. Barcelona: UOC.Orduña-Malea, E., Delgado López-Cózar, E., Serrano-Cobos, J., & Romero, N. L. (2015). Disclosing the network structure of private companies on the web. Online Information Review, 39(3), 360-382. doi:10.1108/oir-11-2014-0282Orduña-Malea, E., Torres-Salinas, D., & Delgado López-Cózar, E. (2015). Hyperlinks embedded in twitter as a proxy for total external in-links to international university websites. Journal of the Association for Information Science and Technology, 66(7), 1447-1462. doi:10.1002/asi.23291Ortega, J. L., & Aguillo, I. F. (2011). Social Network Tools for the Assessment of the University Web Performance. Social Media Tools and Platforms in Learning Environments, 185-201. doi:10.1007/978-3-642-20392-3_11Luis Ortega, J., & Aguillo, I. F. (2013). Network visualisation as a way to the web usage analysis. Aslib Proceedings, 65(1), 40-53. doi:10.1108/00012531311297177Paniagua, J., & Sapena, J. (2014). Business performance and social media: Love or hate? Business Horizons, 57(6), 719-728. doi:10.1016/j.bushor.2014.07.005Romero-Frías, E. (2011). Googling Companies-a Webometric Approach to Business Studies. Leading Issues in Business Research Methods, vol. 1, 93- 106.Romero, D. M., Galuba, W., Asur, S., & Huberman, B. A. (2011). Influence and passivity in social media. Proceedings of the 20th international conference companion on World wide web - WWW ’11. doi:10.1145/1963192.1963250Rybalko, S., & Seltzer, T. (2010). Dialogic communication in 140 characters or less: How Fortune 500 companies engage stakeholders using Twitter. Public Relations Review, 36(4), 336-341. doi:10.1016/j.pubrev.2010.08.004Shu, Z. (2015). How do technical companies use microblogging?. Twente; University of Twente, p. 300.Stieglitz, S.; Krüger, N. (2011). Analysis of Sentiments in Corporate Twitter Communication –A Case Study on an Issue of Toyota. 22nd Australasian conference on information systems - ACIS 2011 Proceedings, pp. 1-11 [paper 29]. Sydney, Australia: ACIS. http://aisel.aisnet.org/acis2011/29 [fecha de consulta: 12-03-2015]Thelwall, M. (2004). Link analysis: An information science approach. Amsterdam: Elsevier.Vaughan, L. (2004). Exploring website features for business information. Scientometrics, 61(3), 467-477. doi:10.1023/b:scie.0000045122.93018.2aVaughan, L., & Romero-Frías, E. (2012). Exploring Web keyword analysis as an alternative to link analysis: a multi-industry case. Scientometrics, 93(1), 217-232. doi:10.1007/s11192-012-0640-xVaughan, L., & Wu, G. (2004). Links to commercial websites as a source of business information. Scientometrics, 60(3), 487-496. doi:10.1023/b:scie.0000034389.14825.bcVaughan, L., & Yang, R. (2013). Web traffic and organization performance measures: Relationships and data sources examined. Journal of Informetrics, 7(3), 699-711. doi:10.1016/j.joi.2013.04.005Vaughan, L., & You, J. (2006). Comparing business competition positions based on Web co-link data: The global market vs. the Chinese market. Scientometrics, 68(3), 611-628. doi:10.1007/s11192-006-0133-xVaughan, L., & You, J. (2010). Word co-occurrences on Webpages as a measure of the relatedness of organizations: A new Webometrics concept. Journal of Informetrics, 4(4), 483-491. doi:10.1016/j.joi.2010.04.005Wamba, S. F., & Carter, L. (2013). Twitter Adoption and Use by SMEs: An Empirical Study. 2013 46th Hawaii International Conference on System Sciences. doi:10.1109/hicss.2013.577Williams, S. A., Terras, M. M., & Warwick, C. (2013). What do people study when they study Twitter? Classifying Twitter related academic papers. Journal of Documentation, 69(3), 384-410. doi:10.1108/jd-03-2012-0027Zimmer, M., & Proferes, N. J. (2014). A topology of Twitter research: disciplines, methods, and ethics. Aslib Journal of Information Management, 66(3), 250-261. doi:10.1108/ajim-09-2013-008

Visualising the intellectual and social structures of digital humanities using an invisible college model

This thesis explores the intellectual and social structures of an emerging field, Digital Humanities (DH). After around 70 years of development, DH claims to differentiate itself from the traditional Humanities for its inclusiveness, diversity, and collaboration. However, the ‘big tent’ concept not only limits our understandings of its research structure, but also results in a lack of empirical review and sustainable support. Under this umbrella, whether there are merely fragmented topics, or a consolidated knowledge system is still unknown. This study seeks to answer three research questions: a) Subject: What research topics is the DH subject composed of? b) Scholar: Who has contributed to the development of DH? c) Environment: How diverse are the backgrounds of DH scholars? The Invisible College research model is refined and applied as the methodological framework that produces four visualised networks. As the results show, DH currently contributes more towards the general historical literacy and information science, while longitudinally, it was heavily involved in computational linguistics. Humanistic topics are more popular and central, while technical topics are relatively peripheral and have stronger connections with non-Anglophone communities. DH social networks are at the early stages of development, and the formation is heavily influenced by non-academic and non-intellectual factors, e.g., language, working country, and informal relationships. Although male scholars have dominated the field, female scholars have encouraged more communication and built more collaborations. Despite the growing appeals for more diversity, the level of international collaboration in DH is more extensive than in many other disciplines. These findings can help us gain new understandings on the central and critical questions about DH. To the best of the candidate’s knowledge, this study is the first to investigate the formal and informal structures in DH with a well-grounded research model

Pla de màrqueting i visibilitat digital de la revista BID

Màster en Gestió de Continguts Digitals, Facultat de Biblioteconomia i Documentació, Universitat de Barcelona i UPF, curs 2014-2015. Tutor: Dr. Mario Pérez-Montoro (UB)Amb la generalització de l’ús d’Internet per a la investigació científica (edició electrònica, cercadors, agregadors, bases de dades), el màrqueting digital esdevé una tècnica essencial per augmentar la visibilitat i el creixement de les revistes digitals. La producció científica ha augmentat exponencialment en les darreres dècades, de forma que els investigadors, saturats d’informació, han de ser selectius a l’hora de llegir noves publicacions i cada vegada tenen més dificultats per detectar quines són més rellevants o transcendents. A aquest fet es suma que ja no s’accedeix directament a la producció científica, sinó que els rastrejadors dels diferents motors de cerca fan d’intermediaris indexant els resultats de la recerca de forma automatitzada. En aquest context, la tasca dels editors va més enllà de publicar continguts de qualitat per als seus lectors, ara també han de publicar continguts optimitzats per a aquests rastrejadors. El SEO (Search Engine Optimization), la presència en xarxes socials i l’optimització de les webs que allotgen aquesta producció científica esdevenen tècniques imprescindibles per arribar als lectors interessats en els continguts que es publiquen. Els articles de la revista BiD: Textos universitaris de biblioteconomia i documentació es troben difosos en aquesta quantitat ingent d’informació i, des de l’equip editorial es planteja la necessitat d’emprendre mesures per a ubicar la revista a la web i fer-la visible per a aquells usuaris que puguin trobar els seus continguts interessants. Objectius Davant el repte d’esdevenir visible en un entorn com el que hem presentat, aquest treball planteja un pla de màrqueting i visibilitat digital que permeti a la revista BiD augmentar la seva visibilitat tan a nivell nacional com internacional, augmentar l’abast dels seus articles i fidelitzar els seus lectors. Amb totes aquestes actuacions, es pretén de forma indirecta augmentar l’impacte tan de la revista com dels articles que conté en la comunitat científica. Propostes finals Tenint en compte que l’objectiu últim d’aquest treball és que BiD adquireixi més rellevància entre la comunitat científica, hem fet una recerca exhaustiva dels sistemes de mesura d’aquesta rellevància. Per això les propostes de millora no només van lligades a l’augment de cites, sinó a l’augment del tràfic a la revista i ús dels seus articles i a les altmètriques que mesuren el nombre de mencions en marcadors socials, xarxes socials científiques i generals. Es proposen actuacions relacionades directament amb la millora del posicionament de BiD com són la unificació de dominis existents, la optimització del rendiment de la web, la descripció de les imatges amb textos alternatius i la definició d’un sistema de URLs amigables. A més, es plantegen actuacions per millorar la interrelació amb bases de dades científiques i cercadors acadèmics, per augmentar la visibilitat de la revista en l’entorn científic. Aquestes millores van vinculades a la implementació d’un sistema de metaetiquetes optimitzades per a aquests entorns i a la creació d’un perfil específic de la revista a Google Scholar Citations. Una altra estratègia per augmentar la visibilitat a la comunitat científica és establir un sistema d’intercanvi de bàners amb revistes i entitats relacionades a BiD per configurar una xarxa d’enllaços de qualitat que remetin tràfic a la revista. Per obtenir la interacció dels lectors i poder conèixer les seves necessitats amb més profunditat es planteja també un pla de xarxes socials genèriques i especialitzades per a científics. Aquesta relació culminarà amb un nou sistema de email marketing que permetrà analitzar i l’engagement dels enviaments. Finalment, com a projecte a mig-llarg termini es proposa afegir l’anglès com a segona llengua de la revista de forma progressiva, començant per afavorir la publicació d’articles que adjuntin el text en anglès

Hyperlinks embedded in Twitter as a proxy for total external inlinks to international university websites

"This is the peer reviewed version of the following article: Orduña‐Malea, E., Torres‐Salinas, D., & Delgado López‐Cózar, E. (2015). Hyperlinks embedded in twitter as a proxy for total external in‐links to international university websites. Journal of the Association for Information Science and Technology, 66(7), 1447-1462., which has been published in final form at http://doi.org/10.1002/asi.23291. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."Twitter as a potential alternative source of external links for use in webometric analysis is analyzed because of its capacity to embed hyperlinks in different tweets. Given the limitations on searching Twitter’s public application programming interface (API), we used the Topsy search engine as a source for compiling tweets. To this end, we took a global sample of 200 universities and compiled all the tweets with hyperlinks to any of these institutions. Further link data was obtained from alternative sources (MajesticSEO and OpenSiteExplorer) in order to compare the results. Thereafter, various statistical tests were performed to determine the correlation between the indicators and the possibility of predicting external links from the collected tweets. The results indicate a high volume of tweets, although they are skewed by the performance of specific universities and countries. The data provided by Topsy correlated significantly with all link indicators, particularly with OpenSiteExplorer (r = 0.769). Finally, prediction models do not provide optimum results because of high error rates. We conclude that the use of Twitter (via Topsy) as a source of hyperlinks to universities produces promising results due to its high correlation with link indicators, though limited by policies and culture regarding use and presence in social networks.Orduña Malea, E.; Torres-Salinas, D.; Delgado López-Cózar, E. (2015). Hyperlinks embedded in Twitter as a proxy for total external inlinks to international university websites. Journal of the American Society for Information Science and Technology. 66(7):1447-1462. doi:10.1002/asi.23291S1447146266