Evolution of the Field of Social Media Research through Science Maps (2008-2017)

The objectives of this work were to discover the main points of interest in the field of research on Social Media, within the scientific area of Communication, and to analyse how it has evolved. A methodology based on the analysis of co-words and visualisation techniques was applied. The data was obtained from scientific publications indexed in the Web of Science (WoS) database, during the periods 2008-2012 and 2013-2017. The resulting maps showed that, during the period 2008-2012, the main areas of interest were web 2.0 and the internet in terms of social networking sites. However, during the period 2013-2017, there was a strong upward trend in the impact of social networks and platforms, especially Twitter and Facebook, in many areas (such as social movements, public relations and publicity, distribution of content, crisis communication, participatory journalism, political communication, or the configuration of public identities through social platforms, with special emphasis on youth). Finally, new scientific challenges were found in automatic analysis of content and management of big data. In conclusion, it was possible to transform a complex, underlying, dynamic and multidimensional reality into visible representations that could help experts in the field to better understand the evolution of research on Social Media

Nanotechnology Publications and Patents: A Review of Social Science Studies and Search Strategies

This paper provides a comprehensive review of more than 120 social science studies in nanoscience and technology, all of which analyze publication and patent data. We conduct a comparative analysis of bibliometric search strategies that these studies use to harvest publication and patent data related to nanoscience and technology. We implement these strategies on 2006 publication data and find that Mogoutov and Kahane (2007), with their evolutionary lexical query search strategy, extract the highest number of records from the Web of Science. The strategies of Glanzel et al. (2003), Noyons et al. (2003), Porter et al. (2008) and Mogoutov and Kahane (2007) produce very similar ranking tables of the top ten nanotechnology subject areas and the top ten most prolific countries and institutions.nanotechnology, research and development, productivity, publications, patents, bibliometric analysis, search strategy

Qualitative Environmental Health Research: An Analysis of the Literature, 1991-2008

BACKGROUND. Recent articles have advocated for the use of qualitative methods in environmental health research. Qualitative research uses nonnumeric data to understand people's opinions, motives, understanding, and beliefs about events or phenomena. OBJECTIVE. In this analysis of the literature, I report the use of qualitative methods and data in the study of the relationship between environmental exposures and human health. DATA SOURCES. A primary search on ISI Web of Knowledge/Web of Science for peer-reviewed journal articles dated from 1991 through 2008 included the following three terms: qualitative, environ*, and health. Inclusion and exclusion criteria are described. DATA EXTRACTION. Searches resulted in 3,155 records. Data were extracted and findings of articles analyzed to determine where and by whom qualitative environmental health research is conducted and published, the types of methods and analyses used in qualitative studies of environmental health, and the types of information qualitative data contribute to environmental health. DATA SYNTHESIS. Ninety-one articles met inclusion criteria. These articles were published in 58 different journals, with a maximum of eight for a single journal. The results highlight a diversity of disciplines and techniques among researchers who used qualitative methods to study environmental health, with most studies relying on one-on-one interviews. Details of the analyses were absent from a large number of studies. Nearly all of the studies identified increased scientific understanding of lay perceptions of environmental health exposures. DISCUSSION AND CONCLUSIONS. Qualitative data are published in traditionally quantitative environmental health studies to a limited extent. However, this analysis demonstrates the potential of qualitative data to improve understanding of complex exposure pathways, including the influence of social factors on environmental health, and health outcomes.National Institute of Environmental Health Sciences (R25 ES012084, P42ES007381

Evolution of the Field of Social Media Research through Science Maps (2008-2017)

The objectives of this work were to discover the main points of interest in the field of research on Social Media, within the scientific area of Communication, and to analyse how it has evolved. A methodology based on the analysis of co-words and visualisation techniques was applied. The data was obtained from scientific publications indexed in the Web of Science (WoS) database, during the periods 2008-2012 and 2013-2017. The resulting maps showed that, during the period 2008-2012, the main areas of interest were web 2.0 and the internet in terms of social networking sites. However, during the period 2013-2017, there was a strong upward trend in the impact of social networks and platforms, especially Twitter and Facebook, in many areas (such as social movements, public relations and publicity, distribution of content, crisis communication, participatory journalism, political communication, or the configuration of public identities through social platforms, with special emphasis on youth). Finally, new scientific challenges were found in automatic analysis of content and management of big data. In conclusion, it was possible to transform a complex, underlying, dynamic and multidimensional reality into visible representations that could help experts in the field to better understand the evolution of research on Social Media.Los objetivos de este trabajo fueron descubrir los principales focos de interés del campo de investigación de los Social Media, dentro del área científica de la Comunicación, y analizar la dinámica de su evolución. Se aplicó una metodología basada en el análisis de co-palabras y en técnicas de visualización. Los datos se obtuvieron de las publicaciones científicas indexadas en la base de datos Web of Science (WoS), durante los períodos temporales 2008-2012 y 2013-2017. Los mapas resultantes mostraron que durante el período 2008-2012 las principales áreas de interés fueron la web 2.0 y el uso de Internet en el ámbito de los medios de comunicación. Sin embargo, durante el período 2013-2017 se apreció una fuerte tendencia ascendente del impacto de las redes y las plataformas sociales, especialmente Twitter y Facebook, en numerosas áreas, tales como los movimientos sociales, las relaciones públicas y la publicidad, la difusión de contenidos, la comunicación de crisis, el periodismo participativo, la comunicación política o la configuración de las identidades públicas a través de las plataforma sociales, con especial incidencia en los adolescentes. Por último, los nuevos retos científicos se situaron en el análisis automático de contenidos y en la gestión de datos masivos, o big data. En conclusión, se consiguió transformar una realidad compleja, subyacente, dinámica y multidimensional en representaciones visibles que podrían ayudar a una mejor comprensión de la evolución del campo de investigación de los Social Media por parte de los expertos en la materia

Research opportunities for argumentation in social networks

Nowadays, many websites allow social networking between their users in an explicit or implicit way. In this work, we show how argumentation schemes theory can provide a valuable help to formalize and structure on-line discussions and user opinions in decision support and business oriented websites that held social networks between their users. Two real case studies are studied and analysed. Then, guidelines to enhance social decision support and recommendations with argumentation are provided.This work summarises results of the authors joint research, funded by an STMS of the Agreement Technologies COST Action 0801, by the Spanish government grants [CONSOLIDER-INGENIO 2010 CSD2007-00022, and TIN2012-36586-C03-01] and by the GVA project [PROMETEO 2008/051].Heras Barberá, SM.; Atkinson, KM.; Botti Navarro, VJ.; Grasso, F.; Julian Inglada, VJ.; Mcburney, PJ. (2013). Research opportunities for argumentation in social networks. Artificial Intelligence Review. 39(1):39-62. doi:10.1007/s10462-012-9389-0S3962391Amgoud L (2009) Argumentation for decision making. Argumentation in artificial intelligence. Springer, BerlinAnderson P (2007) What is Web 2.0? Ideas, technologies and implications for education. JISC Iechnology and Standards Watch reportBentahar J, Meyer CJJ, Moulin B (2007) Securing agent-oriented systems: an argumentation and reputation-based approach. In: Proceedings of the 4th international conference on information technology: new generations (ITNG 2007), IEEE Computer Society, pp 507–515Buckingham Shum S (2008) Cohere: towards Web 2.0 argumentation. In: Proceedings of the 2nd international conference on computational models of argument, COMMA, pp 28–30Burke R (2002) Hybrid recommender systems: survey and experiments. User Model User-Adapt Interact 12:331–370Cartwright D, Atkinson K (2008) Political engagement through tools for argumentation. In: Proceedings of the second international conference on computational models of argument (COMMA 2008), pp 116–127Chesñevar C, McGinnis J, Modgil S, Rahwan I, Reed C, Simari G, South M, Vreeswijk G, Willmott S (2006) Towards an argument interchange format. Knowl Eng Rev 21(4):293–316Chesñevar CI, Maguitman AG, Gonzàlez MP (2009) Empowering recommendation technologies through argumentation. Argumentation in artificial intelligence. Springer, Berlin, pp 403–422García AJ, Dix J, Simari GR (2009) Argument-based logic programming. Argumentation in artificial intelligence. Springer, BerlinGolbeck J (2006) Generating predictive movie recommendations from trust in social networks. In: Proceedings of the fourth international conference on trust management, LNCS, vol 3986, 93–104Gordon T, Prakken H, Walton D (2007) The Carneades model of argument and burden of proof. Artif Intell 171(10–15):875–896Guha R, Kumar R, Raghavan P, Tomkins A (2004) Propagating trust and distrust. In: Proceedings of the 13th international conference on, World Wide Web, pp 403–412Heras S, Navarro M, Botti V, Julián V (2009) Applying dialogue games to manage recommendation in social networks. In: Proceedings of the 6th international workshop on argumentation in multi-agent aystems, ArgMASHeras S, Atkinson K, Botti V, Grasso F, Julián V, McBurney P (2010a) How argumentation can enhance dialogues in social networks. In: Proceedings of the 3rd international conference on computational models of argument, COMMA, vol 216, pp 267–274Heras S, Atkinson K, Botti V, Grasso F, Julián V, McBurney P (2010b) Applying argumentation to enhance dialogues in social networks. In: ECAI 2010 workshop on computational models of natural argument, CMNA, pp 10–17Karacapilidis N, Tzagarakis M (2007) Web-based collaboration and decision making support: a multi-disciplinary approach. Web-Based Learn Teach Technol 2(4):12–23Kim D, Benbasat I (2003) Trust-related arguments in internet stores: a framework for evaluation. J Electron Commer Res 4(2):49–64Kim D, Benbasat I (2006) The effects of trust-assuring arguments on consumer trust in internet stores: application of Toulmin’s model of argumentation. Inf Syst Rese 17(3):286–300Laera L, Tamma V, Euzenat J, Bench-Capon T, Payne T (2006) Reaching agreement over ontology alignments. In: Proceedings of the 5th international semantic web conference (ISWC 2006)Lange C, Bojãrs U, Groza T, Breslin J, Handschuh S (2008) Expressing argumentative discussions in social media sites. In: Social data on the web (SDoW2008) workshop at the 7th international semantic web conferenceLinden G, Smith B, York J (2003) Amazon.com recommendations: item-to-item collaborative filtering. IEEE Internet Comput 7(1):76–80Linden G, Hong J, Stonebraker M, Guzdial M (2009) Recommendation algorithms, online privacy and more. Commun ACM, 52(5)Mika P (2007) Ontologies are us: a unified model of social networks and semantics. J Web Semant 5(1):5–15Montaner M, López B, de la Rosa JL (2002) Opinion-based filtering through trust. In: Cooperative information agents VI, LNCS, vol 2446, pp 127–144Ontañón S, Plaza E (2008) Argumentation-based information exchange in prediction markets. In: Proceedings of the 5th international workshop on argumentation in multi-agent systems, ArgMASPazzani MJ, Billsus D (2007) Content-based recommendation systems. In: The adaptive web, LNCS, vol 4321, pp 325–341Rahwan I, Zablith F, Reed C (2007) Laying the foundations for a world wide argument web. Artif Intell 171(10–15):897–921Rahwan I, Banihashemi B (2008) Arguments in OWL: a progress report. In: Proceedings of the 2nd international conference on computational models of argument (COMMA), pp 297–310Reed C, Walton D (2007) Argumentation schemes in dialogue. In: Dissensus and the search for common ground, OSSA-07, volume CD-ROM, pp 1–11Sabater J, Sierra C (2002) Reputation and social network analysis in multi-agent systems. In: Proceedings of the 1st international joint conference on autonomous agents and multiagent systems, vol 1, pp 475–482Schafer JB, Konstan JA, Riedl J (2001) E-commerce recommendation applications. Data Min Knowl Discov 5:115–153Schafer JB, Frankowski D, Herlocker J, Sen S (2007) Collaborative filtering recommender systems. In: The adaptive web, LNCS, vol 4321, pp 291–324Schneider J, Groza T, Passant A (2012) A review of argumentation for the aocial semantic web. Semantic web-interoperability, usability, applicability. IOS Press, Washington, DCTempich C, Pinto HS, Sure Y, Staab S (2005) An argumentation ontology for distributed, loosely-controlled and evolvInG Engineering processes of oNTologies (DILIGENT). In: Proceedings of the 2nd European semantic web conference, ESWC, pp 241–256Toulmin SE (1958) The uses of argument. Cambridge University Press, Cambridge, UKTrojahn C, Quaresma P, Vieira R, Isaac A (2009) Comparing argumentation frameworks for composite ontology matching. in: Proceedings of the 6th international workshop on argumentation in multi-agent systems, ArgMASTruthMapping. http://truthmapping.com/Walter FE, Battiston S, Schweitzer F (2007) A model of a trust-based recommendation system on a social network. J Auton Agents Multi-Agent Syst 16(1):57–74Walton D, Krabbe E (1995) Commitment in dialogue: basic concepts of interpersonal reasoning. State University of New York Press, New York, NYWalton D, Reed C, Macagno F (2008) Argumentation schemes. Cambridge University Press, CambridgeWells S, Gourlay C, Reed C (2009) Argument blogging. Computational models of natural argument, CMNAWyner A, Schneider J (2012) Arguing from a point of view. 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Mapping utopian art: alternative political imaginaries in new media art (2008-2015)

This thesis investigates the proliferation of alternative political imaginaries in the Web-based art produced during the global financial crisis of 2008 and its aftermath (2008- 2015), with a particular focus on the influence of communist utopianism. The thesis begins by exploring the continuous relevance of utopianism to Western political thought, including the historical context within which the financial crisis of 2008 occurred. This context has been defined by the new political, social and cultural milieu produced by the development of Data Capitalism – the dominant economic paradigm of the last two decades. In parallel, the thesis identifies the “organic” connections between leftist utopian thought and networked technologies, in order to claim that the events of 2008 functioned as a catalyst for their reactivation and expansion. Following this analysis, the thesis focuses on how politically engaged artists have reacted to the global financial crisis through the use of the World Wide Web. More specifically, the thesis categorises a wide range of artworks, institutional and non-institutional initiatives, as well as theoretical texts that have either been written by artists, or have inspired them. The result of this exercise is a mapping of the post-crisis Web-based art, which is grounded on the technocultural tools employed by artists as well as on the main concepts and ideals that they have aimed at materialising through the use of such tools. Furthermore, the thesis examines the interests of Data Capitalists in art and the Internet, and the kinds of restrictions and obstacles that they have imposed on the political use of the Web in order to safeguard them. Finally, the thesis produces an overall evaluation of the previously analysed cultural products by taking into account both the objectives of their creators and the external and internal limitations that ultimately shape their character. Accordingly, the thesis locates the examined works within the ideological spectrum of Marxist and post-Marxist thought in order to formulate a series of proposals about the future of politically engaged Web-based art and the ideological potentialities of networked communication at large

When the Social Meets the Semantic: Social Semantic Web or Web 2.5

The social trend is progressively becoming the key feature of current Web understanding (Web 2.0). This trend appears irrepressible as millions of users, directly or indirectly connected through social networks, are able to share and exchange any kind of content, information, feeling or experience. Social interactions radically changed the user approach. Furthermore, the socialization of content around social objects provides new unexplored commercial marketplaces and business opportunities. On the other hand, the progressive evolution of the web towards the Semantic Web (or Web 3.0) provides a formal representation of knowledge based on the meaning of data. When the social meets semantics, the social intelligence can be formed in the context of a semantic environment in which user and community profiles as well as any kind of interaction is semantically represented (Semantic Social Web). This paper first provides a conceptual analysis of the second and third version of the Web model. That discussion is aimed at the definition of a middle concept (Web 2.5) resulting in the convergence and integration of key features from the current and next generation Web. The Semantic Social Web (Web 2.5) has a clear theoretical meaning, understood as the bridge between the overused Web 2.0 and the not yet mature Semantic Web (Web 3.0).Pileggi, SF.; Fernández Llatas, C.; Traver Salcedo, V. (2012). When the Social Meets the Semantic: Social Semantic Web or Web 2.5. Future Internet. 4(3):852-854. doi:10.3390/fi4030852S85285443Chi, E. H. (2008). The Social Web: Research and Opportunities. Computer, 41(9), 88-91. doi:10.1109/mc.2008.401Bulterman, D. C. A. (2001). SMIL 2.0 part 1: overview, concepts, and structure. IEEE Multimedia, 8(4), 82-88. doi:10.1109/93.959106Boll, S. (2007). MultiTube--Where Web 2.0 and Multimedia Could Meet. IEEE Multimedia, 14(1), 9-13. doi:10.1109/mmul.2007.17Fraternali, P., Rossi, G., & Sánchez-Figueroa, F. (2010). Rich Internet Applications. IEEE Internet Computing, 14(3), 9-12. doi:10.1109/mic.2010.76Lassila, O., & Hendler, J. (2007). Embracing «Web 3.0». IEEE Internet Computing, 11(3), 90-93. doi:10.1109/mic.2007.52Dikaiakos, M. D., Katsaros, D., Mehra, P., Pallis, G., & Vakali, A. (2009). Cloud Computing: Distributed Internet Computing for IT and Scientific Research. IEEE Internet Computing, 13(5), 10-13. doi:10.1109/mic.2009.103Mangione-Smith, W. H. (1998). Mobile computing and smart spaces. IEEE Concurrency, 6(4), 5-7. doi:10.1109/4434.736391Greaves, M. (2007). Semantic Web 2.0. IEEE Intelligent Systems, 22(2), 94-96. doi:10.1109/mis.2007.40Bojars, U., Breslin, J. G., Peristeras, V., Tummarello, G., & Decker, S. (2008). Interlinking the Social Web with Semantics. IEEE Intelligent Systems, 23(3), 29-40. doi:10.1109/mis.2008.50Definition of Web 2.0http://www.oreillynet.com/pub/a/oreilly/tim/news/2005/09/30/what-is-web-20.htmlZhang, D., Guo, B., & Yu, Z. (2011). The Emergence of Social and Community Intelligence. Computer, 44(7), 21-28. doi:10.1109/mc.2011.65Pentlan, A. (2005). Socially aware, computation and communication. Computer, 38(3), 33-40. doi:10.1109/mc.2005.104Staab, S., Domingos, P., Mika, P., Golbeck, J., Li Ding, Finin, T., … Vallacher, R. R. (2005). Social Networks Applied. IEEE Intelligent Systems, 20(1), 80-93. doi:10.1109/mis.2005.16The Semantic Webhttp://www.scientificamerican.com/article.cfm?id=the-semantic-webDecker, S., Melnik, S., van Harmelen, F., Fensel, D., Klein, M., Broekstra, J., … Horrocks, I. (2000). The Semantic Web: the roles of XML and RDF. IEEE Internet Computing, 4(5), 63-73. doi:10.1109/4236.877487OWL Web Ontology Language Overviewhttp://www.w3.org/TR/owl-features/Vetere, G., & Lenzerini, M. (2005). Models for semantic interoperability in service-oriented architectures. IBM Systems Journal, 44(4), 887-903. doi:10.1147/sj.444.0887Fensel, D., & Musen, M. A. (2001). The semantic web: a brain for humankind. IEEE Intelligent Systems, 16(2), 24-25. doi:10.1109/mis.2001.920595Shadbolt, N., Berners-Lee, T., & Hall, W. (2006). The Semantic Web Revisited. IEEE Intelligent Systems, 21(3), 96-101. doi:10.1109/mis.2006.62Dodds, P. S., & Danforth, C. M. (2009). Measuring the Happiness of Large-Scale Written Expression: Songs, Blogs, and Presidents. Journal of Happiness Studies, 11(4), 441-456. doi:10.1007/s10902-009-9150-9Pang, B., & Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations and Trends® in Information Retrieval, 2(1–2), 1-135. doi:10.1561/1500000011Thelwall, M., Buckley, K., & Paltoglou, G. (2011). Sentiment strength detection for the social web. Journal of the American Society for Information Science and Technology, 63(1), 163-173. doi:10.1002/asi.21662Blogmeterhttp://www.blogmeter.it/Christakis, N. A., & Fowler, J. H. (2010). Social Network Sensors for Early Detection of Contagious Outbreaks. PLoS ONE, 5(9), e12948. doi:10.1371/journal.pone.0012948Jansen, 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.21149Bernal, P. A. (2010). Web 2.5: The Symbiotic Web. International Review of Law, Computers & Technology, 24(1), 25-37. doi:10.1080/13600860903570145Mikroyannidis, A. (2007). Toward a Social Semantic Web. Computer, 40(11), 113-115. doi:10.1109/mc.2007.405Jung, J. J. (2012). Computational reputation model based on selecting consensus choices: An empirical study on semantic wiki platform. Expert Systems with Applications, 39(10), 9002-9007. doi:10.1016/j.eswa.2012.02.03

Information Sources and Cartography

U članku su opisani informacijski izvori na internetu, svrstani u tri skupine: bibliografske baze podataka (Bibliographia Cartographica, GEOPHOKA, Scopus i Current Contents (CC)), citatne baze podataka (Web of Science: Thomson Reutersa (Science Citation Index Expanded (SCIE), Social Science Citation Index (SSCI) i Arts & Humanities Citation Index (A&HCI)) i baze podataka s cjelovitim tekstom uključujući elektroničke časopise. U bibliografskim bazama podataka analizirana je zastupljenost kartografskih sadržaja. Pretraživanjem baze CC dobiveni su podaci o kartografima s više od 10 članaka. Prema citatnoj bazi Web of Science dani su podaci o kartografima s najvećim ukupnim brojem citata iz članaka objavljenih od 1955. do kraja 2008. godine uz dodatni uvjet da je svaki rad bar jednom citiran u razdoblju 2000 –2008. Dani su i podaci o dva najčešće citirana kartografska članka u posljednjih 50 godina. S pomoću pretraživača PERO (web-servis knjižnice Instituta Ruđer Bošković) dan je popis kartografskih i njima srodnih elektroničkih časopisa i elektroničkih verzija tiskanih časopisa s cjelovitim tekstom koji su dostupni hrvatskoj akademskoj i znanstvenoj zajednici.The paper describes Internet information sources divided into following three groups: bibliographic databases, citation databases and databases with full texts including electronic journals. Bibliographic databases Bibliographia Cartographica, GEOPHOKA, Scopus and Current Contents (CC) are analyzed concerning cartographic content representation. Searching the Current Contents database resulted in data about cartographers with more than 10 papers in CC journals. According to the Web of Science citation database, data are given about the most cited cartographers in papers published during the period between 1955 and the end of 2008 on the condition that each paper was cited at least once between 2000 and 2008. Data are also given about two most cited cartographic papers in the last 50 years. The PERO browser (web service of the Ruđer Bošković Institute) was used to make a list of cartographic and related electronic journals and electronic versions of printed journals with full text available to Croatian academic and scientific community

Informacijski izvori i kartografija

The paper describes Internet information sources divided into following three groups: bibliographic databases, citation databases and databases with full texts including electronic journals. Bibliographic databases Bibliographia Cartographica, GEOPHOKA, Scopus and Current Contents (CC) are analyzed concerning cartographic content representation. Searching the Current Contents database resulted in data about cartographers with more than 10 papers in CC journals. According to the Web of Science citation database, data are given about the most cited cartographers in papers published during the period between 1955 and the end of 2008 on the condition that each paper was cited at least once between 2000 and 2008. Data are also given about two most cited cartographic papers in the last 50 years. The PERO browser (web service of the Ruđer Bošković Institute) was used to make a list of cartographic and related electronic journals and electronic versions of printed journals with full text available to Croatian academic and scientific community.U članku su opisani informacijski izvori na internetu, svrstani u tri skupine: bibliografske baze podataka (Bibliographia Cartographica, GEOPHOKA, Scopus i Current Contents (CC)), citatne baze podataka (Web of Science: Thomson Reutersa (Science Citation Index Expanded (SCIE), Social Science Citation Index (SSCI) i Arts & Humanities Citation Index (A&HCI)) i baze podataka s cjelovitim tekstom uključujući elektroničke časopise. U bibliografskim bazama podataka analizirana je zastupljenost kartografskih sadržaja. Pretraživanjem baze CC dobiveni su podaci o kartografima s više od 10 članaka. Prema citatnoj bazi Web of Science dani su podaci o kartografima s najvećim ukupnim brojem citata iz članaka objavljenih od 1955. do kraja 2008. godine uz dodatni uvjet da je svaki rad bar jednom citiran u razdoblju 2000–2008. Dani su i podaci o dva najčešće citirana kartografska članka u posljednjih 50 godina. S pomoću pretraživača PERO (web-servis knjižnice Instituta Ruđer Bošković) dan je popis kartografskih i njima srodnih elektroničkih časopisa i elektroničkih verzija tiskanih časopisa s cjelovitim tekstom koji su dostupni hrvatskoj akademskoj i znanstvenoj zajednici

Social Commerce Adoption Model

In recent years the emergence of Web 2.0has brought changes in businesses. It may be observed as a paradigm shift in business (Wigand, et al., 2008). It has affected e-commerce, resulting in the emergence of a new concept known as social commerce. This has also led to changes within many business plans in online markets. Drawing on the Technology Acceptance Model (TAM) (Davis, 1989) the author analyses some of the components of social commerce which affect the intention to buy among individuals by proposing and testing Social Commerce Adoption Model (SCAM). Most research undertaken in the area of social commerce has been descriptive and lacks a solid theoretical foundation. This research gathers survey data and applies structural equation modelling (SEM) to analyse the data. Participation on forums and communities and perceived usefulness are shown to positively impact the trust, leading to more intention to buy among consumers