Tag: knowledge-management

  • Small World Information Bubbles

    Small World Information Bubbles

    Small World Information Bubbles

    Information Bubbles

    We all live in an information bubble. Not because we are unaware of alternative perspectives, but because we prefer the perspectives of our “tribe” (or in-group).
    Fox News, CNN, and MSNBC are filling the trust hole left by eroding community life. Increasingly, extremist online media groups and politicized TV networks are exploiting the vacuum left by abolishing the fairness doctrine. There is no requirement for media sources to be balanced or objective in their presentation of news or facts [1].

    In the 1970s, 80s, and 90s research demonstrated that people only read newspapers that aligned with their political point-of-view (Knobloch-Westerwick et al, 2019). Now people seek out media, TV, and online news sources that align with their existing perspective – or are served with reinforcing points of view via social media filtering mechanisms.

    A filter bubble is the state of intellectual isolation that arises when personalized searches, recommendation systems, and algorithmic curation selectively presents information to each individual user (Pariser, 2011).

    Elfreda Chatman’s “Small World” Findings

    Elfreda Chatman (1991) showed how people in working class and marginalized communities prefer news from friends & neighbors to external sources. She described the world that less-educated or impoverished individuals inhabit, using six aspects of information-seeking. Chatman argues that poor and less-educated individuals tend to:

    1. Live life in a small world

    Information originating outside of their local circle of contacts holds little of interest for the lower class. Their information access is driven by the combination of living in a risky environment, life at the margin of influence and social participation, and “the awareness that if one wants acceptance, future goals and aspirations must be constrained by the standards of one’s family and friends.”

    2. Have lower expectations of success

    People in marginalized and poorer communities believe their success is governed by luck rather than opportunity or skill.

    3. Seek information only from direct or trusted contacts

    People (generally) prefer to seek information mainly from others like themselves, and are skeptical of claims not personally experienced. They view external perceptions about reality as not adequate, trustworthy, or reliable, which limits exposure to new possibilities or education.

    4. Have a limited-time horizon

    Their lifestyle is present rather than future focused. They base decisions on “the immediate present and the very recent past” rather than planning for the future.

    5. Have an insider’s worldview

    People in marginalized and poorer communities view the outside world as unpredictable and hostile. There is an “us vs. them” mentality, where people residing outside of one’s familiar surroundings are viewed with suspicion.

    6. Use the mass media differently than do higher socioeconomic classes.

    Marginalized people are heavy television viewers: “mass media, particularly television, is viewed as a medium of escape, stimulation, and fantasy” rather than an information source. They perceive news to be a reflection of events that occur locally and so they are more likely to be “mistrustful of others and afraid of being victims of crime.” They keep dogs and guns for protection.

    Chatman’s (1991) Small World theory has proved highly influential, as shown in Figure 1. This theory has been used to demonstrate how – because evaluating information in an online world is so complex – people tend to rely on members of their local community, or online influencers trusted by local community members, as sources of reliable information (Chowdhury & Chowdhury, 2013).

    Life in the round theory influence network

    Figure 2. Influence of Chatman’s “Small World” Information Theory
    (Gonza´lez-Teruel & Abad-Garcı´a, 2018)

    Chatman’s “small world” theory explains why Fox News is so subversive to society: it markets itself as the sole purveyor of truth and plays on distrust of people outside the group by pretending that their privileged journalists are just like “ordinary people.” Members of marginalized and poorer communities consume news as a medium of entertainment – they are relatively uneducated and can be indoctrinated without realizing it, as this Fox News presents perspectives from “people like us.” When trying to get a broadcast license in the UK, from where they were banned, Fox News described their content as entertainment, rather than news.

    Filter Bubbles in Online Communities

    Because social media and news media are driven by algorithm or network-connected interaction, they create a “small world” network for everyone, regardless of social class. On social media platforms, algorithms and the need to develop networks of regular social contacts can inadvertently isolate a user into an ideological filter bubble (Pariser, 2011), by only serving them information that it thinks they want to see. For example, Meta (Facebook, Instagram, and Threads) curate their posts to match them to posts on similar topics, or containing similar keywords and sentiment-related modifiers that users have sought out previously [2]. If you “like” posts from a particular perspective, those are all that you will see. Two examples of filtering mechanisms are:

    • On Threads, a Meta social media site which uses a preference-oriented algorithm to display posts for each user, there has been a lot of discussion about how the algorithm rewards people who “like” posts to sympathize with those whose dog or cat has just died, with a depressing, never-ending stream of posts about dead or dying pets.
    • On platforms with no filtering algorithm, such as Bluesky, the need to follow other users in order to obtain visibility and online-interaction imposes its own filter bubble, as people tend to follow those with similar perspectives to their own (people whose posts they enjoy reading).

    This creates an online small-world – an automated filter-bubble. Because of their limited, ideological information preferences, it is difficult to introduce people to alternative points of view. They see alternative ideological viewpoints – including factual support for counter-perspectives – as dishonest or subversive. When confronted by cognitive dissonance, they reframe the “facts” to fit with their beliefs, because of the importance of local community perspectives in their world. They engage in defense mechanisms such as avoidance, denial, or cherry-picking sources. Dissonance research has demonstrated that people are more willing to examine materials that confirm their beliefs than materials that dispute their beliefs. reinforcing their filter-bubble (and confirming research from previous decades). People become isolated in a filter-bubble of limited information sources, of which they are largely unaware.

    Diagram representing an online filter bubble allowing some types of information through, but not others.

    Figure 2. In an ideological filter bubble, indicated by the circle, exchange of information is closed, limited to a prescribed network of influences, and insulated from rebuttal (Wikipedia)

    Social media algorithms and network-association mechanisms (such as following people whose posts you prefer) can inadvertently isolate a user into an ideological filter bubble, by only serving them information that it thinks they want to see. It is important to actively seek out diverse sources of information and – when countering disinformation in a community – to introduce countervailing information (such as data on the efficacy of vaccination) via trusted community influencers, rather than presenting people with external, unvouched for scientific evidence.

    Notes

    [1] Kellyanne Conway, a public relations and media influencer working for Donald Trump, famously coined the phrase “alternative facts” to reflect ideological perspectives for which there was no objective evidence.
    https://en.wikipedia.org/wiki/Alternative_facts

    [2] An example of sentiment-analysis is associating a modifier such as “demented” with a keyword such as “president.” Posts containing both terms will be ranked as more attractive to the user than posts without them, if the user has “liked” posts with similar sentiment-terms previously.

    Reference

    Chatman, E. A. (1991). Life in a small world: Applicability of gratification theory to information-seeking behavior. Journal of the American Society for Information Science, 42, 438–449.
    https://doi.org/10.1002/(SICI)1097-4571(199107)42:6<438::AID-ASI6>3.0.CO;2-B

    Chowdhury, G. G., & Chowdhury, S. (2013). Human information behaviour studies and models. In Information Users and Usability in the Digital Age (pp. 55–84). Facet Publishing.
    https://doi.org/10.29085/9781856049757.004

    Gonza´lez-Teruel & Abad-Garcı´a (2018) The influence of Elfreda Chatman’s theories: a citation context analysisScientometrics (2018) 117:1793-1819
    https://doi.org/10.1007/s11192-018-2915-3

    Harmon-Jones, E., & Harmon-Jones, C. (2007). Cognitive dissonance theory after 50 years of development. Zeitschrift für Sozialpsychologie, 38(1), 7-16. Downloaded 5/12/2026 from
    https://www.researchgate.net/profile/Eddie-Harmon-Jones/publication/255581596_Cognitive_Dissonance_Theory_After_50_Years_of_Development/links/638e8e53484e65005be6c4a8/Cognitive-Dissonance-Theory-After-50-Years-of-Development.pdf

    Knobloch-Westerwick, S., Westerwick, A., & Sude, D. J. (2019). Media choice and selective exposure. In Media effects (pp. 146-162). Routledge. Downloaded 5/12/2026 from
    https://kimliaa.wordpress.com/wp-content/uploads/2021/10/routledge_communication_series_mary_beth_oliver_arthur_a._raney_jennings_bryant_-_media_effects__adv.pdf#page=157

    Pariser, E. (2011). The filter bubble: How the new personalized web is changing what we read and how we think. Penguin.

    Wikipedia (2015) Filter bubble. Accessed 5/12/2026 at https://en.wikipedia.org/wiki/Filter_bubble. Graphic source Original: Evbestie Vector: Dabmasterars, CC BY-SA 4.0 https://creativecommons.org/licenses/by-sa/4.0, via Wikimedia Commons

  • Designing Social Media Platforms For Online Learning

    Designing Social Media Platforms For Online Learning

    Recently, I have been using a new social media platform to run one of my classes. The idea was, that as we are studying social informatics, we could study the effect of using social media on our own workflows first hand. I also thought that – in these days of daily Facebook and Twitter use – a social media site would add some relevance to the class. My thinking was that the “right-brain” expression that Daniel Pink  extolls as critical to motivation in the 21st Century – the design, narrative, synthesis, empathy, play and sensemaking skills – would be enabled by the use of social media (Pink, 2005). The site has a WIKI, blogs, discussion forums, and an interactive chat facility. I was proposing that we used Google+ hangout for short class discussions by video. For the first week, I set students the task to post to the WIKI, to post to their own blog, to locate some web readings, and to join Google+ if they had not already done so.

    By Thursday (from a Monday start), almost all of the students had posted to the discussion forum. Several had asked me questions by email. But no-one had posted to the Blog or the WIKI. By Friday, two of the more technologically-literate students had made blog posts. But most of the activity was still on the discussion forums – and only three students had provided me with Google+ contact details. Then I started to question my own assumptions. All of the students had used Blackboard for their online course access, which revolves around an asynchronous discussion board. So they were used to interacting via an asynchronous forum. I had assumed that they would be excited to use more “social” media for class interactions or for sharing what they had discovered about the topic. But how did this fit into their idea of how they would behave in an online class? Very badly. Most students sign up for online courses because this provides them with choices about what to do, when. They have a low learning-curve for using a discussion forum. Anything else is hard work.

    Clay Shirky talks about the cognitive surplus that is available from zillions of digitally-literate people with mundane jobs and untapped creativity. He argues that this expresses itself in the groundswell of free, open source software initiatives and in the crowdsourcing phenomenon (Shirky, 2010). But graduate students with a full-time job are already using their cognitive surplus in grappling with new areas of learning. My assumption that they may have some left over for experimenting with social media may be false. The problem is that the learning curve gets in the way of the “right-brain” expression that I wanted to encourage. I may need to rethink how far experimenting with social media is constraining people’s’ ability to express themselves.

    References
    Daniel Pink  (2005) A Whole New Mind: Why Right-Brainers Will Rule the Future. Berkely Publishing: New York.
    Pink (2005) Revenge Of The Right Brain, Wired Magazine, Feb. 2005.
    Clay Shirky (2010) Cognitive Surplus: Creativity and Generosity in a Connected Age, Penguin Press: New York.
    Clay SHirky (2010) An Extract From Cognitive Surplus. Wired Magazine, Business Video, June 16, 2010.
    Clay Shirky and Daniel Pink  (2010) Cognitive Surplus: The Great Spare-Time Revolution. Wired Magazine, June 2010.

  • Organizational Coordination

    Organizational Coordination

    I have been working for a while on comparing the results from some very complex research studies of collaborative design in groups that span disciplines or knowledge domains. I was stunned to realize that I had different types of group activity depending on the sort of organization.

    By “organization,” I mean the way in which work is organized, not the sort of business they are in. I noted three types or organization, that seem to respond to collaboration in different ways:

    • Tightly-coupled work organizations rely on well-defined work roles and responsibilities to coordinate tasks across group members. When people in this sort of group have to make decisions, they partition these decisions, based on expertise. Because they all know each others’ capabilities and roles, they don’t have to think about who-knows-what: this is just obvious. This type of organization falls down when people don’t perform their role reliably. For example, if the whole system relies on accurate information coming into the group, someone who misinterprets what they observed can undermine the whole group system.
    • Event-driven organizations rely on external crises and pressures to coordinate group action. People in this sort of group have strongly-defined roles in the wider organization that take precedence over their role in the group — for example in management taskforce groups, business managers tend to prioritize their other work over problems that the group needs to fix. When people in this sort of group make decisions, they partition these decisions according to who-claims-to-know-what, who has time to do the work, and who knows people connected to the problem. They get to know each others’ capabilities over time, but this is a slow process as priorities and decisions are driven by external events, rather than a shared perception of what needs to be done. This type of organization falls down when decisions or actions that were put on a back burner because of another crisis inevitably become a crisis themselves because they were not followed through.
    • Loosely-coupled organizations rely on ad hoc work roles and cooperation among group members. This type of group is commonest in business process change groups, professional work-groups, and community groups, where people are there because they share an interest in the outcome.  When people in this sort of group make decisions, they partition these decisions according to who can leverage external connections to find things out and who has an interest in exploring what is involved. People often share responsibilities in these groups, comparing notes to learn about the situation. This type of organization falls down because it is hard to coordinate. So shared tasks are performed badly because someone knew something vital that they failed to communicate back to the group.
    Why would we care about these different types of organization? Well these structures affect how we approach problem-solving and design. If we (process and IS analysts) need to work with one of the tightly-coupled work-groups, we need to identify who has the decision-making capability for what. It would not occur to a tightly-coupled group member that anyone would not realize who to go to for what. If we need to work with an event-driven group, we have to realize that our work will not be a priority for them -- it must be made a priority by gaining an influential sponsor who can kick a$$ within the group(!).  If we work with a loosely-coupled group, we need to engage the interest of the group as a whole. Working with individuals can lead to failure, as this type of group makes decisions collaboratively, not on the basis of knowledge or expertise.
    Coordinating group work can be like taming wild horses

    Why would we care about these different types of organization? Well these structures affect how we approach problem-solving and design. If we (process and IS analysts) need to work with one of the tightly-coupled work-groups, we need to identify who has the decision-making capability for what. It would not occur to a tightly-coupled group member that anyone would not realize who to go to for what. If we need to work with an event-driven group, we have to realize that our work will not be a priority for them — it must be made a priority by gaining an influential sponsor who can kick a$$ within the group(!).  If we work with a loosely-coupled group, we need to engage the interest of the group as a whole. Working with individuals can lead to failure, as this type of group makes decisions collaboratively, not on the basis of knowledge or expertise.

    I have a fair amount of evidence for this line of thought and I am pursuing other factors that make these groups different. More to follow …