Abstract

LinkedIn, that massive professional networking site we all know, has totally changed how we connect in our work lives. But we have to ask at what cost? In this paper, I have taken a look at LinkedIn through Hampton’s idea of ‘persistent and pervasive’ communities and found that despite connecting an incredible 1.1 billion people worldwide, LinkedIn is slowly throttling real community building by obsessing over metrics and algorithms. It has us chasing likes and shares like we’re teenagers on Instagram, instead of fostering genuine connections. If you look closely at the quality of exchanges, they are superficial at best, there’s no real engagement. Throughout this paper, I look at how professionals are trying to please the omnipresent algorithm while still making contributions that actually matter and share some practical ways to navigate the platform from my own experiences and current research. I’ll discuss some approaches to balance close professional relationships with broader networking, and how to break free from the limiting echo chambers created by LinkedIn which ultimately limit our perspectives. At the end of the day, professional networking should be about community building rather than just collecting digital gold stars.

Main Paper

With over 1 billion members from more than 200 countries (LinkedIn, 2025), LinkedIn has become “the dominant professional network” (Knight, 2019).  If we look at LinkedIn through the lens of Hampton’s (2016) ‘ persistent and pervasive’ community a different view can start to be formed.  My thesis is that despite LinkedIn’s geographical boundless, seniority-flattened and discipline-agnostic environment, it is driven by algorithms and metrics that dilute what LinkedIn set out to achieve in the first place – “connecting the world’s professionals to make them more productive and successful” (LinkedIn, 2025). I propose this dilution is caused by professionals being touted as creators who chase performative metrics rather than authentic community building.  Therefore, what we want to know is, how are professional communities formed and what influence does LinkedIn’s algorithms and metrics have. Recently, the term “Creator Mode” and “ Gold Top Voices” have recently been removed, the reason for which is unclear, though according to Garla (2025) the removal of the Gold Top Voices may be to generate “more genuine contributions.”  Which poses the question for online communities, do you have to be a ‘creator’ to be effective on LinkedIn? To explore these topics I will look at LinkedIn from the view of Hampton’s (2016) persistent networks and pervasive awareness, the metric validation of professional identity, communities of practice, the dilution of professional communities, strategies for building communities and finally the future of professional communities.

Let’s start with our first topic, Hampton’s persistent networks (2016, p. 101), which is described as ‘communication structures’ that allow people to maintain their connections over time. These connections can involve any life event and require minimal effort, time and can enable the reach of entire networks effortlessly. This persistence is juxtaposed to past networks where people lost contact after moving or changing jobs and maintaining contact was much more resource intensive and took the form of in-person conferences, trade events and functions” (Nisonoff, 2020).  LinkedIn through the application of its message history, connection lists and activity logs (posts and comments) can be classified as persistent since it enables professionals to remain connected during job changes, movement across geographical locations locally and internationally, and for the duration of their career and after. LinkedIn’s persistency also has the benefit of opening up networking to people who either didn’t have the resources or position to network, or their field didn’t lend itself to this type of connection (Davis et al., 2020, p. 13). It’s important to note that along with this increased exposure, also comes concerns about privacy and the blurring of personal and professional boundaries (Kelkar & Sinha, 2024). Hampton’s persistence also relates to how professional communities overcome geographical limitations. This presents itself in LinkedIn’s features like global search filters and post translation features which enable professionals to create, build or sustain relationships across continents. Without the LinkedIn platform this would be impossible to sustain because digital persistence eliminates the traditional spatial constraints experienced by the networking approaches of the past. Subsequently networking now becomes “less transitory than any time in modern history” (Hampton, 2016, p. 101).  The benefit of geographical access is that it provides “diverse perspectives, ideas, and opportunities” and this global reach is also beneficial for industries where “international collaboration, such as technology, finance, and marketing” is key (Roberts, 2025).  The second part of Hamptons community framework is pervasiveness, which we’ll discuss next.

Pervasiveness can be described as the omnipresent nature of social media that lets us know what’s happening in people’s lives without us consciously looking for it. Hampton (2016) describes this as happening through “short and asynchronous exchanges” (p. 103) that give us exposure to our networks “interests, location, opinions and activities” (p. 103) without us asking for it. Davis (2020, p. 4) builds on Hampton’s work and describes this as “ambient awareness” and unlike persistency, is all around us, it’s akin to us being planet Earth and the ambience being the Milky Way – albeit a slight exaggeration! In the urban-industrial era, prior to social media and digital technologies, this awareness would have been facilitated by synchronous communication (Hampton, 2016, p. 112) such as phone calls and in person meetings and newsletters. In preindustrial communities this would have relied on word of mouth in densely connected communities (Hampton, 2016, p. 105).  Let’s see how this connects to LinkedIn.

LinkedIn has at its core a form of pervasive awareness that is facilitated by features that shape an individual’s professional network, for example the PYMK (People You May Know) feature (Castillo-de Mesa & Gómez-Jacinto, 2020, p. 104). This matters because this environment and its features shape how our networks are created (p. 103), for better or worse. Whilst I created an analogy that suggested that LinkedIn was akin to a galaxy, perhaps it’s more like the “Truman Show” (Allmovie, n.d.) where the main character lives his life on a colossal sound stage.  There is an assumption by LinkedIn that creating an atmosphere of ambient awareness they are creating meaningful sharing of knowledge and experiences making individuals more productive and successful (Al-Qawasmeh & Saha, 2019, p. 521). A study by Boczkowski et al. (2018) on incidental news consumption, used a practiced-based approach to understand how people engage with information technologies. If we apply this to LinkedIn we can draw a number of connections. First there is a strong connection between the technology and content practices of the users, that is LinkedIn ‘has’ features and people actively ‘use’ these features, such as sharing endorsing and connecting (p. 3533). Second engagement and reading patterns are fragmentary on LinkedIn, which aligns with Boczkowski’s finding that access to news stories happens while people are doing something else (p. 3532). Finally, on LinkedIn whether something is newsworthy is determined by a combination of editorial, algorithms and social filtering (p. 3533), influencing the user’s views and knowledge. Hence, we can see that news and knowledge sharing are heavily curated by LinkedIn, which is what Freelon calls echo chambers (2020, p. 4) or filter bubbles (Packman, 2012). In looking closer at Hampton’s persistent and pervasive awareness framework we can see an important manifestation in how the identity of professionals is validated on LinkedIn, which is through the recognition they receive from others through metrics and algorithms rather than substantive contributions, we will discuss that next.

Our thesis suggests that LinkedIn’s metrics and algorithms are eroding the ability of professionals to be productive and successful. The way this is being enacted is through what Eric Ries  calls vanity metrics, which when coupled with LinkedIn’s algorithms allows “each person to live in their own private reality” (Frank L, 2024; Ries, 2016).  If the focus is on easily manipulated vanity metrics such as, likes, impressions and downloads, that don’t reflect meaningful engagement, then the impact as discussed by Richard Rogers (Rogers, 2018) is three fold. Success is measured by simple counts presented in LinkedIn’s “success theatre” (p. 450) forsaking ‘actionable metrics’ (Frank L, 2024) upon which the effectiveness of contributions and true success measured. The pursuit of the ‘vanity space’ (Rogers, 2018, p. 455) may encourage professionals to be less productive as they perform for the sake of the score and “desire for validation” (Dancsi, 2024). Finally, the pursuit of vanity metrics may lead to a distortion of what is important in an individual’s professional field, that would have otherwise been revealed in ‘critical analytics’ (p. 455) which would potentially provide more meaningful insights. These vanity metrics therefore have the effect of turning professional networking from something of substance into what could be described as persistent visibility that doesn’t have persistent value.  We should acknowledge however, that vanity metrics are a reflection of how people are feeling at that point in time and therefore indicative of trends and people’s mindsets. For example tracking 60 of my own LinkedIn posts (O’Brien, 2025) over a three month period, three posts with the hooks “Investors claim they’re purely rational” had a relatively similar result as the post  “Think of a Pint of Beer” and “I cant believe I just said that”, each talking about delivery skills, analogies, and mindset respectively. There is no rationale as to why these performed better except that they’re what people were interested in at that point in time and could potentially detract from focusing on actionable metrics (Frank L, 2024) that promote professional success. These metrics we will discuss next.

The attribution of metrics to a member’s posts or contributions redefines the way value is determined on LinkedIn. When metrics become the yardstick by which value is measured there is the potential for communities to shift from knowledge sharing to algorithmic obedience, where those little numbers at the end of your post are the only things that matter. This shift is mirrored in the focus on quantifiable interactions, as  Trunfio and Rossi (2021, p. 285)  note, where “the behavioural dimension is still the most used proxy to measure users’ level of engagement” with marketers and social media platforms prioritising “likes, comments and sharing” as key metrics.  In addition to the potential loss of knowledge sharing, there is also the loss of relationships which underpin communities and networks. However as Hampton and Wellman (2018, p. 643) point out this ‘moral panic’ is not new as each generation laments ‘about the loss of community’ that accompanies technological and societal changes.  This tension between vanity metrics and value creation impacts not only professionals but also shapes how Virtual Communities of Practice function through the Group function on LinkedIn.

Communities of Practice in the traditional sense are “groups of people who share a concern, a set of problems, or a passion about a topic, and who deepen their knowledge and expertise by interacting on an ongoing basis” (Noar et al., 2023). If these groups meet in a “digital space to exchange ideas, they are referred to as virtual  communities of practice, or VCoPs for short” (Franc et al., 2024). The primary tool for building VCoPs on LinkedIn is the Group function, which can fragment professional discourse by creating echo chambers (Hampton & Wellman, 2018, p. 644) driven by algorithms that reinforce existing knowledge rather than challenging it (it should be noted that this isn’t the only tool, but the one we will focus on for this discussion). Since professional knowledge development requires exposure to a diversity of views and opinions, anything that restricts that, such as algorithms that push vanity metrics, will be counter to the primary purpose of the VCoP. In a study by Franc et al. (2024) three observations were made that support this claim: “the algorithm can narrow horizons by primarily showing content tailored to one’s own preferences,” “that LinkedIn’s algorithm has a lot of influence, making it challenging to manipulate it according to individual needs,” and “the algorithm may contribute to a lack of diversity in the network and feed, pushing polarising and superficial posts more than detailed, in-depth posts.” However, it should be acknowledged that being part of a LinkedIn Group can bring benefits despite the effect algorithms have. Cinelli et al. (2020, p. 6) found that “information spreading is driven by the interaction paradigm imposed by the specific social media,” meaning that even though algorithms can shape discourse, the patterns of behaviour by professionals can also have a significant impact. This play between algorithms and behaviour highlights a bigger challenge for LinkedIn’s approach to professional communities.

This challenge comes in the form of a fundamental choice to the way professionals either contribute in a meaningful way to the VCoP or creating content the algorithm will promote, which makes it a professional ethical dilemma. This is real for a lot of people as they want to be rewarded for their contribution to a group, not in monetary terms but in accolades. These accolades are a form of social capital which refers to “the resources (information, knowledge, ideas and various supports) embedded in social networks ….that we access through our relationships with others who share common norms and values” (Keles, 2016, p. 318). As with any capital, tangible or not, if people are not getting that from the group then they will look to the platform to provide that capital. This creates the ethical dilemma where professionals must choose between authentic contribution and metric driven visibility, which in turn can lead to the dilution of meaningful professional community ties on the LinkedIn platform.

This dilution of community ties on LinkedIn is a result of the algorithm-driven environment which creates an illusion of any substantive engagement necessary for any meaningful relationships. First, the illusion is created by the platforms ambient nature (Hampton, 2016, p. 103) resulting in emphasis on the quantity  of connections rather than the quality. Additionally, this quantity focus introduces another dimension which is the “cost of caring’ (Hampton, 2016, p. 117). This ‘cost’ presents when professionals are exposed to a continuous stream of activity of others, either the achievement of career milestones or achievements, or the “undesirable events in the lives of others” which can create  “higher levels of stress” for some (Hampton, 2016, p. 117). Furthermore, these asynchronous interactions (Hampton, 2016, p. 111) have the impact of not only creating stress but removing the opportunity for considered real time professional dialogue with LinkedIn’s focus on growth metrics only serving to exacerbate this problem.  Finally, Digital Presenteeism, which is “when you feel the need to always be available online” (Peel, 2020) is an invisible pressure that pushes professionals silently in the ‘pervasive ambience’ of LinkedIn. This constant hidden pressure has the potential to result in ritualistic rather than substantial collaboration, undermining the authentic professional engagement required by effective communities.  The impact of algorithms is highlighted in an article from Pew Research (Rainie & Anderson, 2017) that states “Algorithms create filter bubbles and silos shaped by corporate data collectors; they limit people’s exposure to a wider range of ideas and reliable information and eliminate serendipity.” Even though this article refers to the broader societal impacts of algorithm filtering we can see how it relates to LinkedIn through our discussions so far. Despite these concerns, there is strong evidence that “strong and weak ties predicted informational benefits” reinforcing the “usefulness of social capital” discussed earlier (Utz, 2016).

This social capital can contribute significantly to creating meaningful networks and communities but requires the user to implement purposeful strategies to overcome the constraints we have highlighted so far. These strategies will contribute to help professionals engage in professional networking and enhance their careers. Four strategies that may help are first to develop a balance between what Castillo-de Mesa and Gómez-Jacinto (2020, p. 105) call bridging and bonding social capital. Bonding social capital is created when “ideas and information flow between group members, based on trust between equals,” and bridging social capital is created when knowledge moves from one close group to another, conveying new information and ideas. Second to build ‘communities of practice’ by sharing works in progress and learning journeys and creating “learning partnerships” (Farnsworth et al., 2016, p. 143) related to their area of expertise. Third, focus on solving or contributing to solving the ‘audience problem’ (Hampton, 2016, p. 101) by creating content that has clear target and that encourages reciprocity. Finally, counter Eli Pariser’s  ‘filter bubbles’ (Rowland, 2011, p. 1009) by actively seeking diverse perspectives by using LinkedIn’s hashtags and groups function that create an exposure to viewpoints outside ones immediate network. These approaches require a focus on deliberate practice as I know from my own experience, uptake can be fleeting and random. Whilst having these strategies in mind it is also necessary to be flexible as new approaches come to the fore frequently.

In conclusion, LinkedIn has transformed networking from one bound by geography to a persistent-pervasive community (Hampton, 2016). However there is a juxtaposition of LinkedIn’s mission of making professionals “more productive and successful” (LinkedIn, 2025) and its metrics-driven environment that promotes ‘performative behaviour’ (NeuroLaunch., 2024) over substantive engagement.  It is undeniable that LinkedIn has created an unprecedented global connection between professionals all over the world, that persist throughout career transitions and life events which all play out on what Rogers calls life’s ‘success theatre’ (Rogers, 2018, p. 450). Here value is determined by impression, likes and reposts which have the potential to dilute knowledge exchange and community building.  Nevertheless, professionals can use strategies to curb the vanity metric monster by balancing bridging and bonding social capital creation (Castillo-de Mesa & Gómez-Jacinto, 2020, p. 105), developing genuine ‘communities of practice’ (Farnsworth et al., 2016, p. 143), addressing the ‘audience problem’ (Hampton, 2016, p. 101) and proactively countering ‘filter bubbles’ (Rowland, 2011, p. 1009). As for the future this will depend on how LinkedIn users understand and navigate the performative dimension, and the authentic engagement required to build a professional network.

References

Al-Qawasmeh, A., & Saha, A. (2019). Using AI to build communities around interests on LinkedIn. In (pp. 521-521). ACM. https://doi.org/10.1145/3298689.3346976

Allmovie. (n.d.). The Truman Show. Retrieved 03/03/2025 from https://www.allmovie.com/movie/the-truman-show-am30528#google_vignette

Boczkowski, P. J., Mitchelstein, E., & Matassi, M. (2018). “News comes across when I’m in a moment of leisure”: Understanding the practices of incidental news consumption on social media. New media & society, 20(10), 3523-3539. https://doi.org/10.1177/1461444817750396

Castillo-de Mesa, J. n., & Gómez-Jacinto, L. (2020). Connectedness, engagement, and learning through social work communities on LinkedIn. Intervención psicosocial, 29(2), 103-112. https://doi.org/10.5093/pi2020a4

Cinelli, M., Quattrociocchi, W., Galeazzi, A., Valensise, C. M., Brugnoli, E., Schmidt, A. L., Zola, P., Zollo, F., & Scala, A. (2020). The COVID-19 social media infodemic. Scientific reports, 10(1), 16598. https://doi.org/https://doi.org/10.1038/s41598-020-73510-5

Dancsi, R. (2024). The Narcissistic Leader’s Vanity Metrics. Psychology Today. Retrieved 04/03/2025 from https://www.psychologytoday.com/us/blog/dear-life-please-improve/202409/the-narcissistic-leaders-vanity-metrics

Davis, J., Wolff, H.-G., Forret, M., & Sullivan, S. (2020). Networking via LinkedIn: An examination of usage and career benefits. Journal of Vocational Behavior, 118, 103396. https://doi.org/10.1016/j.jvb.2020.103396

Farnsworth, V., Kleanthous, I., & Wenger-Trayner, E. (2016). Communities of Practice as a Social Theory of Learning: a Conversation with Etienne Wenger. British journal of educational studies, 64(2), 139-160. https://doi.org/10.1080/00071005.2015.1133799

Franc, E., Stampfl, R., & Geyer, B. (2024). Virtual Communities of Practice on Linkedin: A Study on Self-Directed, Work-Related Learning. MAP Education and Humanities, 4, 100-114. https://doi.org/https://doi.org/10.53880/2744-2373.2024.4.100

Frank L. (2024). The False Promise of Vanity Metrics: Navigating the Path to True Business Success. Stream. Retrieved 04/03/2025 from https://getstream.io/blog/vanity-metrics/

Freelon, D., Marwick, A., & Kreiss, D. (2020). False equivalencies: Online activism from left to right. Science, 369(6508), 1197-1201. https://doi.org/doi:10.1126/science.abb2428

Garla, C. (2025). LinkedIn’s Gold Top Voice Badge Is Gone: What Does This Mean for Individuals and Businesses? Pixel Studios. Retrieved 02/02/2025 from https://www.pixel-studios.com/blog/linkedin-top-voice-badge-removal-what-it-means-for-businesses/

Hampton, K. N. (2016). Persistent and Pervasive Community:New Communication Technologies and the Future of Community. American Behavioral Scientist, 60(1), 101-124. https://doi.org/10.1177/0002764215601714

Hampton, K. N., & Wellman, B. (2018). Lost and Saved . . . Again

The Moral Panic about the Loss of Community Takes Hold of Social Media. Contemporary Sociology, 47(6), 643-651. https://www.jstor.org/stable/26585966

Keles, J. Y. (2016). Digital Diaspora and Social Capital. Middle East Journal of Culture and Communication, 9, 315–333. https://doi.org/10.1163/18739865-00903004

Kelkar, A. P., & Sinha, A. A. (2024). Beyond the Profile: Examining Social Media’s Influence on Professional Relationships. International Journal for Multidisciplinary Research, 6(2), 1-19. https://www.ijfmr.com/papers/2024/2/16089.pdf

Knight, M. (2019). Teaching Responsible Social Media Practices in Business and Professional Communication: The Importance of LinkedIn. Business and Professional Communication Quarterly, 82(4), 399-400. https://doi.org/10.1177/2329490619884740

LinkedIn. (2025). About LinkedIn. LinkedIn. Retrieved 02/03/2025 from https://about.linkedin.com/

NeuroLaunch. (2024). Performative Behavior: Unmasking the Social Dynamics Behind Our Actions. NeroLaunch. Retrieved 09/03/2025 from https://neurolaunch.com/performative-behavior/

Nisonoff, E. (2020). The Art of Networking. Medium. Retrieved 02/03/2025 from https://medium.com/@elenanisonoff/the-art-of-networking-f6be9805486f

Noar, A. P., Jeffery, H. E., Subbiah Ponniah, H., & Jaffer, U. (2023). The aims and effectiveness of communities of practice in healthcare: A systematic review. PloS one, 18(10). https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0292343

O’Brien, J. (2025). All Activity. LinkedIn. Retrieved 04/03/2025 from https://www.linkedin.com/in/justinobrien3/recent-activity/all/

Packman, C. (2012). Book Review: The Filter Bubble: What the Internet is Hiding from You by Eli Pariser. The London School of Economic and Political Science. Retrieved 03/03/2025 from https://blogs.lse.ac.uk/lsereviewofbooks/2012/08/23/the-filter-bubble-what-the-internet-is-hiding-from-you/#:~:text=Instead%20of%20giving%20searchers%20the,we%20can%20do%20about%20it

Peel, A. (2020). Digital Presenteeism. GOV.UK. Retrieved 05/03/2025 from https://digitalpeople.blog.gov.uk/2020/10/27/digital-presenteeism/

Rainie, L., & Anderson, J. (2017). Theme 5: Algorithmic categorizations deepen divides. Pew Research Center. Retrieved 05/03/2025 from https://www.pewresearch.org/internet/2017/02/08/theme-5-algorithmic-categorizations-deepen-divides/

Ries, E. (2016). Why Vanity Metrics are Dangerous. The Next Big Idea Club. Retrieved 04/03/2025 from https://nextbigideaclub.com/magazine/ericries-vanity-metrics-dangerous/4781/

Roberts, E. (2025). 9 Key Benefits of Using LinkedIn for Professional Growth. ATSresume AI. Retrieved 02/03/2025 from https://atsresume.ai/blog/key-benefits-using-linkedin-professional-growth

Rogers, R. (2018). Otherwise Engaged: Social Media from Vanity Metrics to Critical Analytics. International journal of communication (Online), 450.

Rowland, F. (2011). The Filter Bubble: What the Internet is Hiding from You. Portal : Libraries and the Academy, 11(4), 1009-1011. https://doi.org/https://doi.org/10.1353/pla.2011.0036

Trunfio, M., & Rossi, S. (2021). Conceptualising and measuring social media engagement: A systematic literature review. Italian Journal of Marketing, 2021(3), 267-292. https://doi.org/10.1007/s43039-021-00035-8

Utz, S. (2016). Is LinkedIn making you more successful? The informational benefits derived from public social media. New media & society, 18(11), 2685-2702. https://doi.org/10.1177/1461444815604143