How does a ‘social science’ or ‘philosophy of science’ perspective on science and technology inform Web Science?

‘A Manifesto for Web Science” (Halford, Pope and Carr, 2010) defines the essential characteristics of this relatively new area of study; Web Science “must be a critical discipline” that “looks both ways to see how the web is made by humans and how humans are made by the web”. This broadly socio-technical approach is derived from studies that critically respond to widely-held ‘positivist’ accounts of ‘Normal Science’. These accounts depict the practice of science as a systematic means of discovering facts about the natural world that inevitably progresses toward improved understandings, and technology as a reasonably uncomplicated application of these discoveries. This classical empiricist argument presents a straightforward worldview within which disinterested scientists seek to objectively develop a body of proven knowledge; they make observations, establish hypotheses, collect data and use these to establish new theories. Technologists play a secondary, essentially pragmatic role and “identify needs, problems, or opportunities, and creatively combine pieces of knowledge to address them” (Sismondo, 2010: 8).

Criticism of this view emerged in the mid-twentieth century, developing Hume’s critique of inductive reasoning (Hume, 1748 [2007]: 26) to establish new ways of thinking about the practice of science and the relationship between science, technology and society.  Originating from theories of falsification (Popper, 1959), ‘epistemological anarchism’ (Feyerabend, 1975) and theories expounding ‘paradigms’ and ‘communities’ as an explanation for scientific and technological progress (Kuhn, 1962), over the past half century this body of thought has developed under the general heading of Science and Technology Studies (STS).

Perceived by some as a threat to the authority and survival of ‘Normal Science’ (Stove, 1982; Theocharis and Psimopoulos, 1987), STS, with its inclusion of non-human as well as human ‘actors’ within its field of view, arguably draws a more nuanced picture of the social construction of science and technology than previous models, and is potentially more suited to the study of the Web.  As a system made up of “decentralised information structures … [and ] informal and unplanned informational links between people, agents, databases, organisations and other actors and resources” (Berners-Lee et al., 2006) analysis of the Web needs to reflect this structure, and employ and develop relevant research methodologies .

The question then arises that if ‘Normal Science’ explanations are not fit for purpose, what should be the proper approach to doing Web Science?

The processes involved in undertaking scientific enquiry are based on methodologies that set parameters for measurement, analysis, evaluation, and iteration. An essential outcome of this activity is the communication of results. Because of the nature of funding, most scientists are ultimately called to account on their ability to provide effective evidence to substantiate their claims (Theocharis & Psimopoulos, 1987: 598). Web scientists must not only convince their peers in their own and other disciplines of their competence, the efficacy of their methods, and of the explanatory or predictive power of their conclusions (Prelli, 1990: 89-90), but also non-experts, whether they are in communities, governments or corporations. Essentially, in a world where positivist thought continues to maintain dominance, web scientists need to adopt methodologies that are accepted as effective, and modes of communication that are persuasive. In this context STS, the study of “… the myriad, daily negotiations among human and non-humans that make up the consensus called technology” (Haraway, 1997) has much to offer practitioners of Web Science.

Kuhn’s recognition that science and technology are essentially socially constructed activities, no different from any other work, had a huge impact on the study of science, technology and society that followed in its wake. The assertion that groups of scientists and by extension, technologists, share common methodologies, modes of communication and interpretations of their work which are constructed in social settings in ways that do not accord with straightforward positivist interpretations, continues to be explored by social scientists and anthropologists.

The common thread of STS is that “technologies … gain sense and significance within everyday activities and ordinary experience’ (Heath, Luff and Svensson, 2003: 77) and various methodologies have and are being developed to explain and deepen our understanding of how science and technology are socially constructed. A significant contribution to these evolving methodologies is the ‘Strong Programme’ of the Sociology of Scientific Knowledge (SSK). Bloor’s ‘four tenets’ establishes a clear research framework. Methodologies should be:

  • Causal – concerned with conditions that bring about beliefs or states of knowledge
  • Impartial – with respect to truth and falsity, rationality or irrationality, success or failure. All sides require explanation.
  • Symmetrical in the style of explanation.
  • Reflexive – applicable to sociology itself. (Bloor, 1991 [1995]: 5).

With its agnosticism toward scientific truths and methodological symmetry, this approach focuses on the work as it is performed, and has an open, naturalistic attitude to science and technological knowledge. It applies the concept of ‘finitism’, in that social forces affect interpretations and rules are adapted when applied to new cases.

Criticisms of the Strong Programme have centred on the tendency of practitioners to overlook the changeable nature of society and to simplify the interests of participants as well as areas of conflict. This leads to problems in demonstrating causal links between beliefs and membership of social groups.

The link between technology, beliefs and membership of social groups is highlighted by explanations of how powerful interests may benefit in the social construction of technology. Langdon Winner asserts that by the adoption of some technologies people are unconsciously coerced into actions that may be against their interests. However while power can be exercised in the “design and arrangement of a device or system” to the potential benefit of individuals who align themselves with powerful institutions, it is by no means given that these technologies have “intractable properties” (Winner, 1986). As Pinch and Bijker convincingly argue in their description of the development of the bicycle, as technologies are brought into the field of practice, users exercise ‘interpretive flexibility’ (Pinch and Bijker 1989). That is, science and technology is essentially a rhetorical operation where inventors design artifacts to solve particular problems with specific uses in mind, but users adapt and modify them to fit many and various unforeseen circumstances.

In terms of web-based technologies for learning, ideas generated within Social Construction of Technology (SCOT) closely align with the concept of affordances. This concept has been adopted by educational studies from Gestalt psychology to describe characteristics of the learning process (Laurillard et al, 2000) often attributed to learning technologies. The basic affordances of an artefact are “fundamental properties that determine just how the thing could possibly be used” (Norman, 1985) which are “usually perceivable directly, without an excessive amount of learning” (Gibson, 1979). For example, research into students use of lecture video recordings has shown that they do not watch entire lectures (as may have been predicted by developers), but fast forward through the material to find content of particular interest to them (Gorissen, Van Bruggen and Jochems, 2011).

The adaptation of technologies to meet various specific needs also opens to question the position that scientists and technologists can be studied as discrete and identifiable communities with shared methodologies and ontologies. Haraway’s exploration of disputes within feminism in the eighties (Haraway, 1991) indicates that categorisation of communities is problematic.

In addition Haraway’s re-evaluation of human-machine symbiosis personified by the ‘cyborg’, a creature often depicted as a threatening in science fiction, represented the construct as an empowering figure. The cyborg concept is revisited twenty years later in the context of the Web as an expression of ‘post-human’ entities brought about by the wide adoption of web technology (Hayles, 2006). Hayles re-imagines the cyborg web as the ‘cognisphere’ – a non-human, or disembodied, network that does not replace the human body but extends it through incorporation into human life practices. Non-human networked and programmable media become ‘cultural cognitions’ as they impact on human sensory-motor functions, cognitive processing, and wider political and economic activity. The individual is no longer an appropriate unit of analysis as these ‘cultural cognitions’ are embodied both in people and their technologies.

In direct response to concerns about the prevalence of social determinism in STS, Actor Network Theory (ANT) replaces artefacts and social relations with “chains which are associations of humans … and non-humans” (Latour, 1991: 110). Latour acknowledges that the processes of science and technology are alike and coins the term ‘technoscience’ to encapsulate both (Latour, 1987: 19) and in a similar manner to the Strong Programme, ANT employs methodological symmetry and makes no hierarchical distinction between the human and non-human.

Actor Network Theory employs three key concepts to describe and analyse the ‘co-evolution’ of technoscience and society:

  • Actor worlds: defines the identities, histories, sizes, theories, and roles that unite the diverse entities (human and non-human) involved in specific areas of study.
  • Translation: “To translate is to speak for, to be indispensable, and to displace.” The researcher ‘delineates the scenario’, ‘problematises’ actions and sets out the terrain that the ‘actor-world’ inhabits. To reach a ‘stable construction’ a process of displacement takes place when the entities under analysis are written up within the context of their physical and social environment.
  • Actor networks: The description of the dynamics and internal structure of actor-worlds which emphasises that the structure is “susceptible to change” (Callon, 1986).

In his analysis of the development of an electric car in France in the 1970s, Callon describes the role of electronic fuel cells within the actor network as a “black box whose operation has been reduced to a few well-defined parameters, gives way to a swarm of new actors: scientists and engineers who claim to hold the key to its functioning”. In this analytical process controversies are divided into a series of other elements as a watch is “dismantled by a jeweller to find out what is wrong” (Callon, 1986: 30).

In the study of the Web, ANT methodology can be used to unpick and analyse the actor world within which heterogeneous entities (individual users, researchers, web protocols, network infrastructure, the National Grid, news media, Mark Zuckerberg etc.) interact on an equal footing with (for example) a social network platform. The object of study is not the actors themselves, but the phenomena which is expressed through the interplay of these components (Barad, 2003).

Latour asserts that with the increasing availability of digital techniques and tools which allow “the tracing and visualization of …social phenomenon” and as digital profiles are changing the definition of what it means to be an individual, it may be more productive to focus on this ‘one level standpoint’, in contrast to exploring how individual decisions impact of social constructions (the ‘two-level standpoint’). Latour’s hypothesis is that significant, deeply entrenched social phenomena may be fruitfully investigated, analysed and evaluated through studying the ‘performance’ of new data mining and visualisation techniques.  “Web 2.0…has turned [one-level standpoint] navigation into a mainstream experience which might be captured in a sentence: the more you wish to pinpoint an actor, the more you have to deploy its actor-network.” (Latour et al., 2012: 591).

Criticism of theories that foreground social construction of technology focus on the lack of utility awareness this understanding brings to those actively involved in the experience (Hacking, 1999: 2), however, STS provides a diverse, eclectic and in-depth range of approaches to the study of the co-evolution of science, technology and society (e.g. the heterogeneity of actors under scrutiny, the equal treatment of human and non-human entities and methodological agnosticism) and indicates the efficacy of rejecting a ‘fixed theory of rationality’ and applying an ‘anything goes’, mixed approach when developing methodologies for Web Science (Feyerabend, 1975: 28). As Haraway asserts:
‘The point is to make a difference in the world, to cast our lot for some ways of life and not others. To do that one must be in the action, be finite and dirty, not transcendent and clean.’ (Haraway, 1997: 36).

In education, as in other fields, it is acknowledged that technology provides “the means through which individuals engage and manipulate both resources and their own ideas” (Hannafin, Land, and Oliver, 1999: 128) but also that “…new technology easily supports a fragmented, informational view of knowledge…and is in danger of promulgating only that.” (Laurillard, 2002: 227). In this environment policy makers require guidance on the potential impact of web technologies (e.g. Jisc, 2013 and New Media Consortium, 2013) which enable educators to develop interventions that orchestrate and scaffold learning. This strongly indicates the necessity for using research and evaluation methods that explore the full range of potential affordances and constraints of web technologies and provide predictive tools that facilitate reliable indicators of future challenges and opportunities.

Therefore a mixed approach that enables researchers to choose appropriate methods, whether it is the randomised trials of the positivist tradition, other quantitative and qualitative methods, or pragmatic evaluation processes is required. In the second half of the last century there have been calls to democratise science and technology (Feyerabend, 1999: 224), and the inclusion of public participation has been shown to “increase[s] the quality and relevance of the research” (Staley et al., 2012). In recent years the validity of employing “multiple evaluators” in heuristic evaluation (Nielson, 2009), user involvement in systematic literature reviews (EPPI Centre, 2013), and public involvement in the research and evaluation of health technologies (NIHR, 2013) indicates increased awareness of the usefulness of non-expert involvement in research practices. This may take the form of ‘crowdsourcing’, for example data collection using Mechanical Turk initiatives (e.g Saunders, Bex and Woods, 2013), ‘citizen science’ interventions (e.g. Crowston and Prestopnik, 2013), online surveys (e.g. De Vera et al., 2010), or the formal engagement of lay panels in the assessment of research options (e.g. Boote et al., 2012).

In 2007 environmental scientist Mike Hulne contributed an article for The Guardian about the role of STS in the study of the changing global climate:

All of us alive today have a stake in the future, and so we should all play a role in generating sufficient, inclusive and imposing knowledge about the future. Climate change is too important to be left to scientists – least of all the normal ones. (Hulme, 2007).

This sentiment applies equally to the study of the Web. In order to develop effective research programmes that disentangle the complex relationships between people and technology, that facilitate better understandings of the impact of changes brought about by our interaction with the Web, and improve the ability to predict the effect of Web-based activity, scientists in the field, informed by STS theories, need to employ wide-ranging, diverse and relevant methodologies.


  • Barad, K., 2003. Posthumanist performativity: towards an understanding of how matter comes to matter. In Signs, 28(3) pp.801-31.
  • Berners-Lee, T., Hall, W., Hendler, J.A., O’Hara, K. , Shadbolt, N.  and Weitzner, D.J., 2006. A Framework for Web Science. In Foundations and Trends in Web Science Vol. 1, No 1 (2006) 1–130 [Online] Available at (Accessed 1 December 2013).
  • Bloor D., 1991. The strong programme. In Knowledge and Social Imagery. Ch 1 [Online] Available at (Accessed 1 December 2013).
  • Boote, J. D., Dalgleish, M., Freeman, J., Jones, Z., Miles, M., and Rodgers, H., 2012. ‘But is it a question worth asking?’A reflective case study describing how public involvement can lead to researchers’ ideas being abandoned. In Health Expectations. [Online] Available at (Accessed 9 December 2012).
  • Callon, M., 1986. The Sociology of an Actor-Network: the Case of the Electric Vehicle. In M. Callon, J. Law and A. Rip (Eds.) Mapping the Dynamics of Science and Technology: Sociology of Science in the Real World. London, Macmillan: 19-34. [Online] Available at (Accessed 29 November 2013).
  • Crowston, K. and Prestopnik, N.R., 2013. Motivation and Data Quality in a Citizen Science Game: A Design Science Evaluation. In System Sciences (HICSS), 2013 46th Hawaii International Conference on , vol., no., pp.450,459. [Online] Available at (Accessed 11 December 2013).
  • De Vera, M. A., Ratzlaff, C., Doerfling, P., & Kopec, J., 2010. Reliability and validity of an internet-based questionnaire measuring lifetime physical activity. American Journal of Epidemiology, 172(10), 1190-1198.
  • EPPI Centre, 2013. Welcome to the EPPI Centre. [Online] Available at (Accessed 9 December 2013).
  • Feyerabend, P., 1975. Against Method: Outline of an Anarchistic Theory of Knowledge. London: Verso.
  • Gibson, J. J., 1979. The Ecological Approach to Visual Perception, Boston: Houghton Mifflin Company.
  • Gorissen, P., Van Bruggen, J.M. and Jochems W., 2011. Analysing the use of recorded lectures by students. Short paper presented during the ALT-C conference in Leeds, UK [Online] Available at (Accessed 25 November 2013).
  • Hacking, I., 1999. The social construction of what? Harvard University Press.
  • Halford, S., Pope, C. and Carr, L., 2010. A Manifesto for Web Science. In, Proceedings of the WebSci10: Extending the Frontiers of Society On-Line, Raleigh, US, 26 – 27 Apr 2010. , 1-6. [Online] Available at (Accessed 5 November 2013).
  • Hannafin, M., Land, S., and Oliver, K., 1999. Open learning environments: Foundations, methods, and models. In C. M. Reigeluth (Ed.), Instructional design theories and models: A new paradigm of instructional theory (Vol. II, pp. 115-140). Mahwah, NJ: Lawrence Erlbaum Associates.
  • Haraway, D.,1991. A Cyborg Manifesto: Science, Technology and Socialist Feminism in the Late Twentieth Century. In D. Haraway (Ed.) Simians, Cyborgs and Women: the Reinvention of Nature. London, Free Association Books: 149-181.
  • Haraway, D. J., 1997. Modest-witness@ second-millennium. Femaleman [Copyright]-meets-oncomouse [Trademark]: Feminism and Technoscience. Psychology Press.
  • Hayles, N. K., 2006. Unfinished Work: From Cyborg to Cognisphere. In Theory, Culture & Society, December 2006 23: 159-166, [Online] Available at (Accessed 5 December 2013).
  • Heath, C., Luff, P., and Svensson, M. S., 2003. Technology and medical practice. In Sociology of Health & illness, 25(3), 75-96. [Online] Available at (Accessed 7 November 2013).
  • Hulme, M., 2007. The appliance of science. In The Guardian. [Online] 14 March. Available at (Accessed 25 November 2013).
  • Hume, D., 2007. An enquiry concerning human understanding. Oxford University Press. Originally published in 1748. [Online] Available at (Accessed 6 November 2013).
  • Jisc, 2013. Jisc Inform: Spotting emerging technologies. Issue 36. [Online] Available at (Accessed 20 November 2013).
  • Kuhn, T. S., 1962. Historical Structure of Scientific Discovery. In Science, 136 (3518), June 1, 1962, 760-764. [Online] Available at (Accessed 7 November 2013).
  • Latour, B., 1987. Science in Action: How to Follow Scientists and Engineers Through Society. Cambridge MA: Harvard University Press.
  • Latour, B., Jensen, P., Venturini, T., Grauwin, S. and Boullier, D., 2012, ‘The whole is always smaller than its parts’ – a digital test of Gabriel Tardes’ monads. The British Journal of Sociology, 63: 590–615. [Online] Available at (Accessed 26 November 2013).
  • Latour, B., 1991. Technology is Society Made Durable. In Law J (Ed.) A Sociology of Monsters? Essays on Power, Technology and Domination, Sociological Review Monograph. London, Routledge: 103-131.
  • Laurillard, D., Stratford, M., Luckin, R., Plowman, L., and Taylor, J., 2000. Affordances for Learning in a Non-Linear Narrative Medium, in Journal of Interactive Media in Education, 2000 (2) [online]. Available at (accessed 28 November 2013).
  • Laurillard, D., 2002. Rethinking university teaching: A conversational framework for the effective use of learning technologies. Psychology Press.
  • National Institute of Health Research, 2013. Evaluation, trials, studies. [Online] Available at (Accessed 10 December 2013).
  • New Media Consortium, 2013. Sparking innovation, learning and creativity. [Online] Available at (Accessed 10 December 2013).
  • Nielson, J., 2009. How to Conduct a Heuristic Evaluation. [Online] Available at (Accessed 10 December 2013).
  • Norman D A (1988) The Design of Everyday Things, New York: Basic Books.
  • Pinch, T. J. and Bijker, W.E., 1989. The Social Construction of Facts and Artifacts: Or How the Sociology of Science and the Sociology of Technology Might Benefit Each Other. In Bijker WE, Hughes TP and Pinch TJ (eds.) The Social Construction of Technological Systems: New Directions in the Sociology and History of Technology. Cambridge, MA, MIT Press.
  • Popper, K., 1959. The logic of scientific discovery. London & New York:Routledge Classics. First published 1959 by Hutchinson & Co.
  • [Online] Available at (Accessed 10 November 2013).
  • Prelli, L. J., 1990. Rhetorical logic and the integration of rhetoric and science. In Communication Monographs. Volume 57, Issue 4, 1990 pages 315-322 [Online] Available at (Accessed 22 November 2013).
  • Saunders, D. R., Bex, P. J., and Woods, R. L., 2013. Crowdsourcing a Normative Natural Language Dataset: A Comparison of Amazon Mechanical Turk and In-Lab Data Collection. In Journal of Medical Internet research, 15(5). [Online] Available at (Accessed 10 December 2013).
  • Sismondo, S., 2010. An Introduction to Science and Technology Studies Oxford, Wiley-Blackwell.
  • Staley, K., Buckland, S. A., Hayes, H. and Tarpey, M., 2012. ‘The missing links’: understanding how context and mechanism influence the impact of public involvement in research. in Health Expectations. [Online] Available at (Accessed 10 December 2013).
  • Stove, D. C., 1982. Popper and after : four modern irrationalists. Oxford : Pergamon Press.
  • Theocharis, T., and Psimopoulos, M., 1987. Where Science has Gone Wrong. In Nature, Vol 329, pp 595-598. [Online] Available at (Accessed 5 November 2013).

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

%d bloggers like this: