ArticleRead (15): User Acceptance of Information Technology: Toward a Unified View

User Acceptance of Information Technology: Toward a Unified View. by Venkatesh, V. Morris, M. G. Davis, G. B. Davis, F. D. In MIS Quarterly, 2003, Vol. 27; No.3, pp 425-478

The current information management issues are primarily based on the behavioral science. The primary goal of Venkatesh et al. (2003) is to accomplish a coherent picture of the main lines of the work on individual acceptance of information technology, and further integrate them into a unified theoretical model: the Unified theory of Acceptance and Use of Technology (UTAUT).

The authors review the theoretical and empirical literature on the information technology acceptance models with valuable discussions on 8 major models. After the work of model comparison, which are identified similarly in roots from theories of psychology and sociology, empirical work concerned with the adjustment of "usage" (the dependent variable) and "the role of intention" (a predictor of behavior) to 32 relevant constructs across 8 models is considered. Data from 4 organizations over a 6-month period with 3 points of measurement is utilized to test these relevant constructs.

Results show that:

First, at least one construct of each model was significant and influential, and there are 7 constructs identified as direct determinants of intention or usage.

Second, several other constructs were significantly fading out.

Third, the key differences are settings in constructs related to social influence between voluntary vs. mandatory settings.

Based on these three empirical findings, 4 key moderators (gender, age, experience and voluntariness of use) are provided to justified four main constructs: (1)performance expectancy, (2) effort expectancy, (3) social influence (4) facilitating conditions. The proposed model was later justified by two new organization data.

Finally. the perceptive reader might recognize some likeness of the four constructs of this UTAUT model with two main constructs of the Online Community Framework (OCF): sociability and usability (de Souza and Preece, 2004).

OCF is based on the theory of Human Computer Interaction and focus on two main dimensions: (1) the analyzing of online community their social interaction within the community (sociability); and (2) the understanding of what will happen at the human-computer interface (usability).

While the UTAUT and associated user behavior models intend to serve to predict user intention and usage as a result to provide prescriptive guidance for organization managers and system designers, the OCF-based analyses as to understand how technology may or must be used to improve usability and sociability and further to prevent problems in computer-mediated communication and social interaction brings about different theoretical perspectives in which the semiotic engineering can be served as a potentially valuableble alternative to view management information systems.

ArticleRead (14): DBpedia: a nucleus for a web of open data

DBpedia: a nucleus for a web of open data, By S. Auer, C. Bizer, G. Kobilarov, J. Lehmann, R. Cyganiak and Z. Ives, The 6th International Semantic Web Conference (ISWC 2007) Busan, Korea, November 2007, in LNCS 4825, pp.722-735


The last 30 years have seen a number of attempts by computer scientists with an interest in information integration research and proceeded alongside efforts in Semantic Web with associated technology developments. However, the current Web is still challenged by these tasks. Auer et al. (2007) in this article attempt to integrate information from across various web systems and make Wikipedia information a machine-readable representation both in structural formats and semantic data sets.

The authors provide a relatively comprehensive overview of existing problems and challenges such as:
(1) Web information has not been fully accessible to a general audience
(2) inconsistency, ambiguity, uncertainty, and data provenance of grass-roots data
(3) the need of using collaborative sharing of dynamic data approaches to build the Semantic Web in grass-roots-style
(4) the need of a new model of structured information representation and management


Extending concepts and approaches from the W3C Linking Open Data community project and extract structured information from Wikipedia, the authors argue in favor of a triple model of Resource Description Framework (RDF) that provides a flexible data model for representing and publishing information on the Web. RDF is a basic foundation to give one or more types to a resource set in triples: (subject, predicate, object) or (subject, property, property value) . RDF triples extracted from data sets, in this DBpedia model, are basic components that can be shared, exchanged, and processed queries in a variety of Semantic Web applications.

Several of the most valuable datasets including articles described with concepts, Infoboxes (data attributed for concepts), categories or article categories using SKOS, Yago Types (instances using YAGO classification), internal page links, as well as RDF links, are provided for download as a set of RDF files which are identified by their own URI reference.

ArticleRead (4) : Collaborative Tagging and Semiotic Dynamics

Collaborative Tagging and Semiotic Dynamics, By C Cattuto, V Loreto, L Pietronero ,Arxiv preprint cs.CY/0605015, 2006
From the Cover: Semiotic dynamics and collaborative tagging, Proceedings of the National Academy of Sciences, 2007 - National Acad Sciences

In “Collaborative Tagging and Semiotic Dynamics”, Cattuto, Loreto and Pietronero set down what a user pattern looks like in a social tagging system through empirical statistic analysis of tag co-occurrence. The Yule-Simon model on probability and statistics basis has been used to investigate the long-term memory of users’ tag-vocabulary activities in one of the social tagging system, del.icio.us. A semiotic conceptual model for the tri-partite graph to structure a post as (user, resource,{tag}) is proposed. Therefore, the tri-partite concept which is original from semiotic dynamic literatures is illustrated in the tile as a highlight.

In order to overcome the need for complexity of experimental data, this analysis procedure employs a tag-centric construction view on del.icio.us system. By factoring out two parameters of (users, resource) and adding the set of time parameter from the post, the results of co-occurrence of tagging activities are shown to be consistent with available theoretical calculations in Power Law and Zipf’s Law. Typical applications of utilizing these two statistical theories are well recognized in phenomenon analysis such as in natural language; self-organization and human activity; access patterns; as well as memory–kernel of cognitive psychology. This joint experiment with the well-proved theories offers an alternative method to explore social tagging phenomenon, and for our review to add value on their ideas and research attentions on user behaviors and semiotic concept.

Controversially, however, the research method is likely to be criticized from the semiotic point of views.

First of all, the confusion of two semiotic schools is presented. The authors intend and develop the tri-partite graph from semiotic dynamic concept which follows Charles Sanders Peirce’s (1839-1914) sign theory remarkably in its basic triadic relation within a sign, namely (Represent, Object, Interpretant). The authors have attempted to adopt this triadic elements and rephrase them from (forms {words}, referents {objects}, meanings {categories}) of Steels and Kaplan (1999) to (user, resource,{tag}) in social tagging concept.

However, the authors’ reference of semiotic dynamic is the work of Ke et.al (2002) who adopts the Ferdinand de Saussure (1857–1913) school of semiotics which takes a sign being constructed within a dual relation (signifier, signified). Since these two semiotic schools have been in debates for decades, the authors adopting these two papers as their definition for semiotic dynamic may lead to confusion in general.

Picture 1: Steels and Kaplan (1999)'s Semiotic Dynamic

Secondly, their proposal for the tag-centric calculation method contradicts their own arguments favoring semantic context. In such context, semantic meaning is supossed to deal with the same Object (the same resource / bookmark in this research) to investigate the relation between different users and users' tags on their co-occurrence. Picture 1 shows the original method for the co-occurrence of items for their semantic meaning in Steels and Kaplan (1999) ‘s semiotic dynamic which the authors have cited from. Picture 2 shows the authors' method for calculating the co-occurrence of tags. Different objects (resources /bookmarks refering to) and different users(interpreters) are ignored in this case. The main focus is on the different tags’ relations, namely frequency and co-occurrence especially in low-high rank tags. Note that our review is not to argue that the authors’ work cannot result in user’s activity patterns since the Power Law and Zipf’s law have been well-proved in such domain. To be specific, if the authors’ work is not in the semiotic dynamic domain, the contradiction may not be this tremendous.



Picture 2: the authors' semiotic dynamic?