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The Web and the Mind

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Slides for my talk at the Bangalore Science Forum, National College, Basavanagudi, February 24, 2016.

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The Web and the Mind

  1. 1. Bangalore Science Forum, February 2016 The Web and the Mind Srinath Srinivasa Web Science Lab IIIT Bangalore http://cds.iiitb.ac.in/wsl
  2. 2. Bangalore Science Forum, February 2016 Outline A brief history of the WWW Models of the Web – Web as a Database/Repository – Web as a Cognitive Extension of us – Web as a socio-cognitive space Social Machines Web Science Abstraction and Expression on the Web Characterizing Online Collectives
  3. 3. Bangalore Science Forum, February 2016 Some Recent News Topics Re-emergence of the free-speech debate Personal liberty, sedition, Sec 66A, annoyance, … “The right to be forgotten” Privacy, accountability, personal liberty, … Net Neutrality Bridging the digital divide, neo-colonialism, “data darwinism”, …
  4. 4. Bangalore Science Forum, February 2016 Some Recent News Topics Re-emergence of the free-speech debate Personal liberty, sedition, Sec 66A, annoyance, … “The right to be forgotten” Privacy, accountability, personal liberty, … Net Neutrality Bridging the digital divide, neo-colonialism, “data darwinism”, … W W WW W W
  5. 5. Bangalore Science Forum, February 2016 A brief history of the WWW 1989 CERN physicist Tim Berners-Lee lays out a proposal for information management called “Mesh” Original proposal available from http://www.w3.org/History/1989/proposa l.html 1990 Berners-Lee changes name to “World Wide Web” while writing code for the Mesh Creates three fundamental building blocks: HTML URL (later called URI) HTTP
  6. 6. Bangalore Science Forum, February 2016 A brief history of the WWW 1990 First web page appears on the Internet 1991 Web available for access to people outside of CERN 1993 WWW code made available for free on a royalty-free basis forever by CERN 1994 Berners-Lee joins MIT to found the World Wide Web Consortium (W3C) Original logo for the WWW Image source: Wikipedia
  7. 7. Bangalore Science Forum, February 2016 A brief history of the WWW Design principles for WWW adopted by the W3C: Decentralization (no one controls content on the web) Non-discrimination (net neutrality) Bottom-up design (Open source, participatory approach to maintaining web code) Universality (Agnostic to computing platforms or hardware) Consensus (Participatory approach to web standards) Source: webfoundation.org
  8. 8. Bangalore Science Forum, February 2016 A brief history of the WWW 1993 Mark Andreessen from NCSA releases Mosaic – the first graphical browser for the web 1994 Andreessen, with two colleagues form Mosaic Communications Corporation and release the first commercial web browser: Netscape Navigator First International WWW conference is organized at CERN in May 1994 1996—2000 Dot com boom (“Get large or get lost” mantra) and birth of several first generation search engines and e-commerce sites (Yahoo, Excite, Lycos, Altavista, Amazon, …)
  9. 9. Bangalore Science Forum, February 2016 A brief history of the WWW 2001—2002 Dot com bust. Major web and Internet companies go bankrupt (Excite, Lycos, Nortel Networks, Worldcom,...) 2002– Web 2.0. Web reinvents itself as a participatory social medium bringing social science and psychology central to thinking about the web.
  10. 10. Bangalore Science Forum, February 2016 Models of the Web The web is unlike any other technology developed so far Unlike say cars or washing machines, there is only one web Is the web a “technology” or a “tool” that we use or is it something else? Notable paradigms of the Web considered by researchers: Very large database Digital library / Repository A cognitive extension of ourselves Participatory socio-cognitive space
  11. 11. Bangalore Science Forum, February 2016 Web as a Database Early approaches (mid '90s) to model the Web Focused on the “semi- structured” nature of the Web and as a special case of managing structured (RDBMS) databases Research objectives: structured and rich query semantics Examples include: [AMM 97], [Eng 98], WebQL An example WebQL query Source: http://en.wikipedia.org/wiki/WebQL
  12. 12. Bangalore Science Forum, February 2016 Web as a Digital Library Shift from: Strict notions of “query” Looser notions of “retrieval” and “relevance” Strict notions of “schema” Looser notions of “ontology” Emphasis still on retrieving information Web still seen as a passive repository of information Examples: [GR+ 97], [HMA 03]
  13. 13. Bangalore Science Forum, February 2016 Web as a Cognitive Extension of Ourselves Rooted in Vannevar Bush's interpretation of hypertext reflecting the way information is organized in human brains Focus on interpreting hyperlinks, rather than (just) data on web pages Hyperlink as a(n): – Relevance indicator – Endorsement – Attention pathway Examples: PageRank [BP 98], HITS [GKR 98] Memex
  14. 14. Bangalore Science Forum, February 2016 Web as a Socio-cognitive Space Most contemporary paradigm for understanding the web Web as an active, participatory, social space – people are no longer users, but participants Shift of emphasis from retrieving information from the web to engaging users with the web The Web uses us as much as we use the Web! Examples: Crowdsourcing, Participatory authoring, Push notifications on social media, Click-baiting, etc. The global mind and superintelligence
  15. 15. Bangalore Science Forum, February 2016 The Socio-cognitive Space Image source: https://www.pinterest.com/pin /4433299610614823/
  16. 16. Bangalore Science Forum, February 2016 Web Science From www.webscience.org “Nothing like the Web has ever happened in all of human history. The scale of its impact and the rate of its adoption are unparalleled. This is a great opportunity as well as an obligation. If we are to ensure the Web benefits the human race we must first do our best to understand it. The Web is the largest human information construct in history. The Web is transforming society. In order to understand what the Web is, engineer its future and ensure its social benefit we need a new interdisciplinary field that we call Web Science.”
  17. 17. Bangalore Science Forum, February 2016 Social Machines Represents a class of environments comprising of interplay between humans and technology Outputs of social machines a result of both human and algorithmic decisions Building blocks of the global socio-cognitive space “The Web is an engine to create abstract social machines” – Tim Berners-Lee, Weaving the Web [BH 09] About Social Machines https://youtu.be/8Iz7ZqSOJGU
  18. 18. Bangalore Science Forum, February 2016 Social Machines
  19. 19. Bangalore Science Forum, February 2016 Web Observatory and Telescope Image source: http://www.iconsmind.com/
  20. 20. Bangalore Science Forum, February 2016 Perspectives towards the Web The Web is an Opportunity The Web is a Threat The Web is.
  21. 21. Bangalore Science Forum, February 2016 Global Socio-cognitive Space Aggregators Twitter diplomacy MOOC Cognition Attention Emotions Mental models Macro Effects MicroEffects
  22. 22. Bangalore Science Forum, February 2016 The Web and the Mind On the micro effects of the global socio-cognitive space
  23. 23. Bangalore Science Forum, February 2016 A (highly) Simplified Model of Cognition Declarative memory Semantic Episodic Procedural memory Reflexes Motor control Active mental model Emotion and limbic subsystem Long-term memory Working memory Frontal lobe Amygdala
  24. 24. Bangalore Science Forum, February 2016 The psychological dimension of the online free-speech debates
  25. 25. Bangalore Science Forum, February 2016 The Free Speech Conundrum
  26. 26. Bangalore Science Forum, February 2016 The Free Speech Conundrum The holy grail of democratic societies – freedom of speech (and expression) – is suddenly at the center of a new found controversy At the core of this debate is a call to distinguish between “free speech” and “bad speech”
  27. 27. Bangalore Science Forum, February 2016 Free Speech and Bad Speech The line is not always clear: Disagreeing with popular opinion (free speech) Supporting/opposing a political party (free speech) Racial slur (bad speech) Inciting mob violence publicly (bad speech) Scholarly writing criticizing government or specific religions (free speech considered bad speech in some places) Artistic depiction that offends religious sentiments (let's not even go there!)
  28. 28. Bangalore Science Forum, February 2016 Characterizing Speech Claim: The free speech versus bad speech debate presents a false dilemma, which can never be completely resolved Need: Semantic characterization of speech and conversations and creating awareness and tool-support for online conversations based on this characterization
  29. 29. Bangalore Science Forum, February 2016 Abstraction and Expression Articulation of our objective understanding of something Communicates an idea Articulation of our subjective feeling about something Communicates an emotion
  30. 30. Bangalore Science Forum, February 2016 Abstraction and Expression Reporting: mostly abstraction Opinion: mix of abstraction and expression Emotional reaction: mostly expression
  31. 31. Bangalore Science Forum, February 2016 Abstraction ● Semantic meta-construct used to build our world view ● Processing is resource intensive (“System 2” in Prospect Theory [KT79] terminology) ● Subject to innate cognitive resistance in assimilation due to factors like bounded rationality and conformance pressures Images source: Wikipedia
  32. 32. Bangalore Science Forum, February 2016 Abstraction and Conformance Asch Conformity Experiments
  33. 33. Bangalore Science Forum, February 2016 Conformance and Diffusion of Ideas Information diffusion is faster in sparsely connected parts of a network, rather than densely connected (entrenched) parts due to conformance effects. Node d in the above figure does not switch to the new idea because of conformance pressures from nodes e, f and g Image Source: [Sri 06]
  34. 34. Bangalore Science Forum, February 2016 Models for Diffusion of Ideas Typically based on an element of “criticality” balancing: ability to communicate new idea, and pressure to conform to existing ideas Example models [EK 10] Percolating clusters Ising model Cluster density based diffusion
  35. 35. Bangalore Science Forum, February 2016 Expression ● Semantic construct encapsulating our emotional state for communication ● Subconsciously affects receiver's emotional state by means of emotional contagion ● Emotional contagion also spreads through the web (Ex: Facebook Experiment [KGH 14]) ● Characteristically different from spread of ideas, which have a natural resistance to assimilation Images source: Wikipedia
  36. 36. Bangalore Science Forum, February 2016 Spread of Emotions Models based on spread of epidemics, useful in modeling spread of emotions Emotions are psychosomatic phenomena causing both cognitive and physical affect Intense emotional states induce a state of trauma that have long range repercussions like PTSD Example epidemic models [EK 10] – SIR (Susceptible-Infected-Recovered/Resistant) useful for modeling spread of intense emotions in a population – SIS (Susceptible-Infected-Susceptible) useful for modeling spread of mild emotions in a population
  37. 37. Bangalore Science Forum, February 2016 Abstraction versus Expression Objective belief Asserts an idea Humans have innate resistance towards ideas thrown at them We need to have an “open mind” to entertain new abstractions Subjective emotion Communicates a feeling Humans have innate “anti- resistance” towards emotions thrown at them We need to be “mindful” of our emotional state to be unaffected by an incoming emotion
  38. 38. Bangalore Science Forum, February 2016 Mental Model Axiomatic framework within which we perform reasoning. Encapsulates underlying assumptions, ground truths and inference rules Active mental model Reasoning and deduction carried out within the framework of the currently active mental model Any input that challenges the currently held mental model usually elicits an emotional reaction (laughter, terror, etc.) Linking Abstractions and Expressions
  39. 39. Bangalore Science Forum, February 2016 Characterizing Online Communication Mental model 1 Mental model 2 Mental model 1 Mental model 2
  40. 40. Bangalore Science Forum, February 2016 Characterizing Online Communication Mental model 1 Mental model 2 Mental model 1 Mental model 2
  41. 41. Bangalore Science Forum, February 2016 Characterizing Online Communication Mental model 1 Mental model 2 End Result? Mental model 1 Mental model 2
  42. 42. Bangalore Science Forum, February 2016 The Intense Online World Online communication tend to be more intense and overwhelming due to following factors: – Lack of coherence between mental models (due to anonymity, asynchrony, solipsism, etc.) – Interplay between abstractive and expressive content in conversation Emotions spread faster than ideas due to anti-resistance Spread of emotions greatly complicates the spread of ideas
  43. 43. Bangalore Science Forum, February 2016 Online Collectives
  44. 44. Bangalore Science Forum, February 2016 Wisdom of Crowds? Not all groups of people form “wise” crowds!
  45. 45. Bangalore Science Forum, February 2016 Coagulation Abstraction and Expression can affect group behaviour in different ways A given abstraction or expression can “coagulate” over a group of people (most people in the group think the same way / most people in the group feel the same way) Coagulation in abstraction and expression can explain some failures of crowdsourcing efforts
  46. 46. Bangalore Science Forum, February 2016 Classification of Groups [SS 15] Some coherence in abstractions (Ex: NPOV, NOR,V for Wikipedia) High coagulation Low coagulation
  47. 47. Bangalore Science Forum, February 2016 Classification of Groups Crowds Group of people having shared attention but no shared abstraction or shared expression Rich in insights due to diverse opinions No major emotional contagion Members act as individuals Pose high cognitive load on members Unstable Wise Crowds Share some common abstraction in the form of “ground rules” to facilitate management of diverse opinions without degenerating
  48. 48. Bangalore Science Forum, February 2016 Classification of Groups Herds Group sharing a common abstraction “Herd mentality” pertains to every member of the group thinking in the same way High in persuasive power Low on collective insight Manipulable by external forces if the characteristics of the herd are known
  49. 49. Bangalore Science Forum, February 2016 Classification of Groups Mobs Groups sharing a common emotional state Common emotional state could be either positive emotion (jubilant football fans) or negative emotion (lynch mobs) Need not have common abstraction (members of an angry mob may each be venting personal frustrations through the mob) Highly unpredictable behaviour
  50. 50. Bangalore Science Forum, February 2016 Classification of Groups Gangs Groups sharing both a common abstraction and common emotion All members of the group think and feel the same way about something Passionate and highly persuasive Common emotion could be positive (The researcher “gang of four” on design patterns) or negative (bandits and other organized criminals) Powerful and highly impactful collective actions
  51. 51. Bangalore Science Forum, February 2016 A Computational Model
  52. 52. Bangalore Science Forum, February 2016 A Computational Model
  53. 53. Bangalore Science Forum, February 2016 A Computational Model User Evaluation Dataset comprising of tweets pertaining to #DelhiPolls, #DelhiElections 35 evaluators given a set of 20 randomly picked tweets Evaluators were asked a set of indirect questions seeking their opinion about coagulation levels of abstractions and expressions
  54. 54. Bangalore Science Forum, February 2016 A Computational Model Evaluation Results
  55. 55. Bangalore Science Forum, February 2016 Free Speech Revisited What appears as the online free speech conundrum is actually a complex phenomenon caused by abstraction, expression, dissonance across mental models and group coherence of abstractions and expressions and amplified by the scale of the Web The issue is not (just) a question of what is or should be legal provisions around online speech We need better models to understand cognitive and emotional aspects of human communication and their impacts on a global scale Linearly extrapolating existing models from social psychology bound to fail because, never before in human history was there a global socio-cognitive conversational space like the Web
  56. 56. Bangalore Science Forum, February 2016 The Web and the Mind The web is affecting what we think and feel – thus molding us at a very fundamental level, offering both opportunities and challenges Our understanding of web-scale cognitive phenomena too premature to advocate any form of social or regulatory solutions Web Science: A rich area of research for enthusiastic and curious minds!
  57. 57. Bangalore Science Forum, February 2016 May you be born in interesting times... -- an ancient Chinese curse Thank You!
  58. 58. Bangalore Science Forum, February 2016 References [AMM 97] G.O. Arocena, A.O. Meldelzon and G.A. Mihaila, Applications of a Web query language, in: Proc. of the 6th International World Wide Web Conference, April 7–11, 1997, Santa Clara, California, USA, http://www6.nttlabs.com/HyperNews/get/PAPER267.html [GR+ 97] Gudivada, V.N.; Raghavan, V.V.; Grosky, William I; Kasanagottu, R., "Information retrieval on the World Wide Web," Internet Computing, IEEE , vol.1, no.5, pp.58,68, Sep/Oct 1997 [BP 98] Sergey Brin and Lawrence Page. 1998. The anatomy of a large-scale hypertextual Web search engine. In Proceedings of the seventh international conference on World Wide Web 7 (WWW7), Philip H. Enslow, Jr. and Allen Ellis (Eds.). Elsevier Science Publishers B. V., Amsterdam, The Netherlands, The Netherlands, 107-117. [Eng 98] Carlos F. Enguix. 1998. Database querying on the World Wide Web: UniGuide, an object-relational search engine for Australian universities. Comput. Netw. ISDN Syst. 30, 1-7 (April 1998), 567-572. DOI=10.1016/S0169-7552(98)00080-4 http://dx.doi.org/10.1016/S0169-7552(98)00080-4 [GKR 98] David Gibson, Jon Kleinberg, and Prabhakar Raghavan. 1998. Inferring Web communities from link topology. In Proceedings of the ninth ACM conference on Hypertext and hypermedia : links, objects, time and space---structure in hypermedia systems: links, objects, time and space---structure in hypermedia systems (HYPERTEXT '98). ACM, New York, NY, USA, 225-234. [HMA 03] Ian Horrocks, Deborah L. McGuinness, and Christopher A. Welty. 2003. Digital libraries and web-based information systems. In The description logic handbook, Franz Baader, Diego Calvanese, Deborah L. McGuinness, Daniele Nardi, and Peter F. Patel-Schneider (Eds.). Cambridge University Press, New York, NY, USA 427-449.
  59. 59. Bangalore Science Forum, February 2016 References [BH 09] Berners-Lee, Tim; J. Hendler (2009). "From the Semantic Web to social machines: A research challenge for AI on the World WideWeb" (PDF). Artificial Intelligence. doi:10.1016/j.artint.2009.11.010. [EK 10] David Easley, Jon Kleinberg. Networks, Crowds and Markets: Reasoning about a Highly Connected World. Cambridge University Press, 2010. [KA 79] Daniel Kahneman and Amos Tversky. "Prospect theory: An analysis of decision under risk." Econometrica: Journal of the Econometric Society (1979): 263- 291. [KGH 14] Kramer, Adam DI, Jamie E. Guillory, and Jeffrey T. Hancock. "Experimental evidence of massive-scale emotional contagion through social networks." Proceedings of the National Academy of Sciences 111.24 (2014): 8788-8790. [SS 15] Nirmal Kumar Sivaraman, Srinath Srinivasa. Abstractions, Expressions and Online Collectives. Proceedings of ACM WebSci 2015, Oxford, UK, June 2015.

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