How Firms Can Manipulate Networks And Its Related Phenomenons

How Firms Can Manipulate Networks And Its Related Phenomenons For Their Own Personal Benefit

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1. Introduction

In today's digital world, networks play a big role in many industries, especially online platforms. The more users a platform has and the more they interact, the more valuable it becomes. When the networks such as Facebook, Google or Amazon gain more users, the services available on these platforms become more beneficial, which in turn, strengthens the position of the platform in the market (Barwise and Watkins, 2018). In the beginning, networks were taken as naturally growing social organisations that were entwined with the process of sharing information. But lately, behavioural economics has reconsidered this and has advanced the concept that firms can ultimately utilise networking structures to their strategic advantage. The preferential attachment which does bias the link towards incumbent hubs, controls of influential connector nodes, restricting interoperability between networks (Knudsen et al., 2021). Also, exploiting the lock-in effects allow the dominant platforms to subtly reshape network development, sometimes in an anti-competitive way.

The platforms, when scaling up their networks, win the race for growth and engagement of the users, raise questions on how the regulation of the communication industries must be balanced to avoid harm to individuals and society. In the absence of intervention, tactics of manipulation applied to dense network structures can create self-fulfilling monopolies with the dynamics of "winner takes all". This in turn, leads to a situation in which there is virtually no competition and consumer choice is limited by default (Farrell and Newman, 2019). However, social gains such as the increased accessibility and engagement stemming from network externalities may necessitate some government intervention so that the laws of the market and the public can be maintained in a fair manner.

This essay highlights the network manipulation behaviors of the major digital platforms and the aspects of these practices that may cause the users to favor one competitor forgetting others or to end up with less agency in their choices. Finally, one of the topics will be about preferential attachment, controlling network hubs, breaking the link of segmented networks, and exploitation of lock-in effect for favoring dominant players. Along this line are the social dynamics carefully monitored and provoked by platforms like herd behavior, bandwagon effect, and status signaling tendencies will also be the focus. Following analysis of the market concentration and level of barriers to entry together with the assessment of their impacts this area will be discussed next. This research can help to raise awareness in the network sector of competitive dynamics and evidence-based policymaking can therefore result.

1.1 Concepts of Networks and Network Effects

Networks consist of structures composed of nodes that can represent the person, organization, computer, or other units interconnected with the links or connections linking these nodes. Social networks evolve gradually during a period of communication between people that create trust, benefit, and cooperation. Economic networks also usually come about by heterogeneity as the trade relations that firms have with suppliers, distributors, partners, and consumer’s investments are being made. During startup of connectivity, node interactions are assumedly arbitrary as the only liaison is environmental factors such as location or organizational structure (Brodie et al., 2019). However, nodes establish themselves as more popular or influential over time with better qualities like social status, professionalism, or central locations. Thus, these locations, which are highly connected hubs, keep on accumulating a significant percentage of the links that are developed as familiarity and reliability stay around this area (Hari and Abdulla, 2023). The "preferential attachment" explains the emergence of the "Spam-free" networks structures, which are widely used in social media, citation networks and technology platforms.

Figure 1 Network Effect 

Source: NFX, 2021

As social networks build up connectivity and social capital, interconnections also change, particularly because of homophiles where people prefer to connect only with those that are like them. Demographic characteristics (age, gender, education, or shared interests, etc.) that serve as social categories are not useful for distinguishing different groups as they only concentrate individuals in the same clusters within the network. Industrial clustering, other than in business, is also common with networks of suppliers, these occur because of shared competences, skills, and resources among specialized nodes in specific regions (Fitjar and Timmermans, 2018). Networks in their turn are because of cumulative processes of random and non-random ties formation which may include preferences for familiar hubs, homophiles association and spatial/industrial clustering. This self-organization in the evolutionary process constitutes the foundation of the social forms which in turn provide for information flow and coordinated activities in society as well.

These networks give nodes a high significance that supports social integration, connectivity and information spinning among surrounding members. Social networks allow individuals a wide range of connectivity sources that offer them a variety of viewpoints, prospects, and knowledge. Economic networks also provide companies to access different products, outsource non-core functions, and organize manufacturing in several locations. Such a sort of movement of ideas, resources, and talent within complex network webs to the largest possible extent allows us to obtain major innovations. Intensive connections of the interwoven, multiple, and repetitive relations do not only strengthen collaboration but collective plans too (Pellicelli, 2018). Sharing the same set of beliefs and values, the sense of trust and reciprocity can be more easily generated, and mutual support is provided quite readily in the small-scaled communities. This is a factor that enables team innovation where each block builds on the previous one resulting in important scientific discoveries and new technology (Nilsen, 2019). As a main indication, networks of professional associations face the same issues of cooperation on research, facilitate reflections between practitioners and develop novelties in specializations.

Despite these important aspects of social networks, well connected network positions grant additional edge because they represent a bridge between otherwise isolated peers for trading between them. "Hubs" that coordinate information flows become increasingly relevant also because, due to their capability to efficiently broker and curate knowledge that is understood as a product of the network as whole, they possess an access to extremely wide networking range (Rycroft‐Smith, 2022). Leaders who join these networks as part of the emerging order can bring about positive outcomes for the networks by bringing the right people together. In this case collaboration and working together and by facilitating the communities towards the best of their potential. Basically, networks have the advantage of personal capabilities because they offer people the opportunity of getting various endless social networks and market products and they would access the money through the social circuits (Azorín et al., 2020). This is effective as it develops cooperation, coordination and the utilization of diverse perspectives that act as building blocks for the combinations that lead to the quick social and economic development of societies that are interconnected.

Network externalities refer to how the value or utility that users derive from goods depends on the number of other users in the network. There are two main types - direct and indirect network effects. Direct network externalities exist when the functionality or usefulness of a technology is directly impacted by how many other individuals are using compatible products. For communication networks like telephone or messaging apps, having more direct contacts on the same platform exponentially multiplies its value, due to the ability to directly connect to others (Gregory et al., 2021). Similarly, the popularity of file formats makes those languages more useful as more people can understand them.

Real-world examples include fax machines becoming more useful as more people owned compatible devices, and VHS triumphing over Betamax due to wider network adoption early on. Positive direct effects reinforce adoption feedback loops, while negative direct externalities occur rarely but can collapse markets, as seen with digital technologies that abandon deprecated platforms. Indirect network externalities emerge when the value of a product is increased by the number of complementary goods and services available for use with it (Springel, 2021). For instance, popularity of Microsoft Windows personal computers ultimately stemmed more from the huge indirect network of available software applications than the base OS itself.

Similarly, adoption of Blu-ray over HD-DVD was influenced by the content and hardware ecosystems supporting each standard. Indirect effects draw in complementary businesses that further enrich the network, as seen with app stores adding value to gadgets, and credit/debit networks increasing the viability of plastic money. However, they also risk lock-ins if proprietary standards deter interoperability between ecosystems. Network effects can also become mixed or conjunctive over time (Haglund and Flydén, 2018). Social media derives both direct utility from connecting with friends, and indirect value from engaging platforms, brands, and content on those friend networks (Onofrei et al., 2022). Online shopping gains direct value from other buyers through reviews and recommendations, and indirect utility from merchants selling diverse inventory and options.

1.2 Strategies for Network Manipulation 

Network theory studies have shown how even minor biases in the way new links form can dramatically impact the overall structure and topology of social and information networks over time. Platform businesses are keenly aware of this preferential attachment phenomenon and strategically design systems to shape network growth circuits to their advantage through positive feedback loops. Google's search rankings provide a prime example. When Google launched it in the late 1990s, a site's search results page rank depended largely on objective relevance metrics like the frequency and proximity of query terms on their pages. However, Google soon recognized that links from other popular, authoritative sites conferred even greater prominence in users' minds as a credibility signal (Lewandowski, 2023). As Google methodically crawled and indexed the entire publicly accessible web, this created a rich-get-richer system where the most linked sites rose to the top through no actual change in content quality.

Consequently, smart web publishers started doing whatever they were able to. To increase their page ranks artificially, they used techniques such as link exchange with popular domains in related niches, or even with more widely linked competitors. Google has over time fine-tuned their formula to include hundreds of other factors, starting from the time spent on a page to mobile friendliness that determines an organic rank for a site. The key to the future of search engine optimization is that linking from high popularity sites will amplify search visibility by the same mechanism remaining (Sharma et al., 2022). As a result, the tendency to favor the established actors occurred more and more and became an endless circle because their content occupied constantly the top search positions that usually drive the maximum number of clicks. Old market players had an advantage as they were already sitting on the “sweet spot” of preferential attaching circuits and new entrants had many vulnerabilities as they were not connected to new alternative pathways to traffic (Veglis and Giomelakis, 2021). A broadening of the domains and page attributes by Google in just forming some popularity aspects resulted in specific market alteration, hence creating competition. 

Digital ecosystems of those platforms that dominate in the digital sphere also make use of preferential attachments effectively for their own purposes. On Amazon, private label brands who pay for their product listings to be alongside third-party sellers’ offers means that they have better chances of seeing their products bumped up thus getting higher visibility and conversion through the enhanced placement of products on the page. YouTube greases the relativity wheel of recommendation through effectively linking new viewers to videos of huge channels that have large followers to achieve the amplifying effect (Chamorro-Premuzic, 2023). As concentration moves on to a few giants, small production houses and upcoming channels find their very existence threatened. At that time, if one’s Facebook News Feed algorithm included signals involving close relatives or large publisher pages that had their devoted fans, it would promote the latter content (See more in Appendix Section). The most likely result is gamer dominance, which effectively discourages alternative points of view that cannot muster an initial circulation to scamper algorithmic commercial domains (Rashidian et al., 2020). While consumers benefit from centralized access to popular information flows, niche communities may feel deprived of platforms to organize and be heard on issues impacting them.

Basically, when big companies use their well-designed algorithms to take advantage of how networks grow, it makes things even more favorable for them. Unfortunately, this can make it hard for new people or smaller groups to join in. Strict regulatory controls can be seen as a solution to the dilemma of generating fair and equitable competition and varied voices as an antithesis to the tendency of the platforms to be “optimized” constantly for popularity and user engagement (Iansiti and Lakhani, 2020). In network theory, “nodes” possessing a central location that connects different communities are called “hubs”, “gatekeepers” or “bridges”. They have greater abilities to influence the direction and flow of information within the network compared to the rest of the nodes (González-Alcaide et al., 2020). Through this strategic investment in such focal points the platforms gain access to extensive and powerful networks either by complete takeover or by buying influential people.

YouTube has become the most popular online video platform and people of different genres, like gamers and musicians, create communities around it. Google bought it in 2006 for $1.65 billion mostly because it is the biggest one (Srinivasan, 2020). YouTube's over a billion user base watches billions of hours every day which makes YouTube boasting two times more audience every single day than cable TV viewers. By seizing the hub, Google fixed preference among the tentacles of the whole YouTube network and money-generation over rival platforms while leaving no direct interoperability link (Bergen, 2022). Therefore, in 2012, Facebook had purchased Instagram for a billion dollars, understanding that it was going to be the connector of the cell phone world sharing pictures. Instagram has a user base of about a billion active users who post nearly 100 million pics daily contributing to what can be described as a very creative and viral core within Facebook's overall social offerings (Macarthy, 2021). Similarly, the consolidation of immense users on the Internet by the leading platforms occurs through the taken over networks. At the same time, other tiny startups are badly prevented from appearing.

Another critical point to control the industry is the power the company has over the standard-setting bodies that determine the technical specifications to be followed too. Apple has outsized power over the whole wireless technologies dominance by holding a leading position in the standard board while also making a groundbreaking device. As for example, the fact that its control of and indefinite delay of the adoption of Bluetooth, Wi-Fi and USB-C affects which mobile peripherals and accessories end up as winners (Teece, 2018). The platforms have deliberately done that, in many cases, to break the interoperability of their networks with those of their competitors, for the purpose of controlling their customers or subscribers. For example, users of WhatsApp apparatus could not transfer their chats to substitute messaging services Signal before due to technical barriers (Nyasulu and Dominic Chawinga, 2019). Dominance and controlling the important network hubs and standards miss the sense of opening and neutrality digital infrastructures were devised for. 

Internet platforms insist on consciously shattering the Internet into the several separate networks that belong to each one of them through different ways such as limiting interoperability between digital ecosystems. This provides them with full control of user attention, profits from subscriptions, and sucks out competition within the networks. With such networks, competitors are regarded as enemies and are excluded to the very end (Terranova, 2022). A major way of how major platforms created framing the early internet was through "walled gardens" such as the App Store and Google play. While mobile application marketplaces emerged as the main distribution paths accessed by 5.36 billion mobile phone users, they have also tightened down their control on third party developers by enforcing their own terms and conditions in addition to their developer agreements (Ortiz Freuler, 2023). This encompassed solely the needed adoption of such in-house payment systems and the virtual transfer of 30% or more of remittance, imposing strict app rules governing the content and data usage policies.

Although creating special app store districts within the core iOS and Android ecosystems, allowing users to easily find an exploding number of apps, came at a price it essentially restricted multi-platform reach as well as underhanded developers’ bargaining power. The app developers were strongly motivated to devote more developers to customize each store's particular technology requirements and user interface patterns as well as risked missing the opportunity of creating cross-platform solutions through standards. Over time, this loose system gained its own momentum and formed two rather independent fiefs, controlled solely by both Apple's and Google's kingdoms (Varoufakis, 2024). They also possess the power to reject multiculturalism and segregate their networks. McDonald and Smith-Rowsey, (2018) stated that granting autonomy of Netflix to pay around $17 billion annually on exclusive licenses a year in advance grants them multi – years buying rights from television and film creating arena for media conglomerates. 

Network segmentations are enforced and even at the interface level via incompatibility. Platforms rely on capturing all the sides of the market, and when there is cross-platform access, they lose the benefits of sticking to all sides of the market. For instance, even though providers get the impression that the users have ownership of their data, this is not the case in platforms like Facebook. They argue that direct logging and payments to competing services which they decline to launch. Interoperable open ordinal management solutions capable of integrating transnational user profiles sitting isolated in separated databases could be one of the solutions brought to the table by the different companies that enforce their own identity rules (Guo, 2023). But this prevents a monopolize in the individual hardware vendors in the marketplace that determines the general business arrangement through proprietors.

1.3 Leveraging Related Phenomena 

The study of networks indicates that people tend to follow the behavior of others which is recognized as social proof or a herding. People are naturally inclined to follow choices that are being made by the majority in the tribe, (since) equality, care and protection may be the most acceptable approach for a group during the early stages of evolution. Online platforms master this craft of tapping into the inner workings of these biases and shaping a popularity contest behavioral dynamic online (Starbird et al., 2019). Desire to be socially valued and to achieve status oftentimes leads to predisposition to expensive and apparent commodity use, with the members of peer groups as the witnessing target group. Places center on this by creating social spheres where trendy sheep follow others in possession of novelties, leading to wealthy circles with lucrative feedback (Kabanda, 2018). Providing leaders with lots of overall positive information, which is then popularized by word-of-mouth and propagates as influencers influence others, is a core element of the methodology behind strategic seeding of networks with influencers of high profiles.

First, luxury goods were the early beneficiaries as those with faster-growing YouTube accounts increased the visibility of luxury products that inherently attract a higher social currency. Just as norms spread by people seeding new games and virtual goods into the most viewed streams on Twitch cause networks to spread behaviors across them, viewers wanting in on trends also take up such behavior. Even narrow-focused matters attract potential users via social learning, as timely AMAs of experts with Reddit ignite a huge stack of questions. Views follow a cascading geometric pattern from the seed of the initial interest (Pearson, 2020). Another element of social proof occurs when certain platforms start recommending popular items which are prominently displayed on very many posts. The platform even goes so far as to feed most popular posts as “trends you might like”, which perpetuates the self-fulfilling mechanism for content that is already reaping the benefits of herding dynamics (Crosby, 2022). Group niche choices are algorithmically tailored to user tendencies based on peer opinion as a meta-crowd, thus creating a self-reinforcing attention economy where collective attention centers on majority views.

The term “bandwagon effect” was a positive feedback loop property that network scientists explained with the phenomenon where the perceived value or utility significantly rises as more individuals decide to be on the particular side. This generates robust self-fulfilling tendencies of heterogeneity resulting in "tipping" of the entire market gradually towards one preferable variant even if it was initially inferior. Realizing these inner psychological tricks, platforms methodically stage elements driven by a bandwagon reaction that works in favor of their own goals (Barnfield, 2021). At the beginning, knowledge ones needed to rise at this point but once a few of its peers joined, friends felt strong FOMO (fear of missing out) pressures that made enrollment close to everyone rather quickly during the semester. Rival where almost no members and eventually disengaged from the conversation, yet FB had self-sustaining and self-amplifying loops that attracted a massive amount of college students to use Facebook as the only social network.

When this platform of YouTube is working, it implements similar seeding methods, like highlighting "Top Trending Videos" on the homepage, where they influence people that they must share further because they are worth it (Foster, 2020). Twitter's retweet mechanism was purposefully enhanced to satisfy the innate instinct to inform other people as well as provoking the rapid spread of the same information cascades initially started with very minor contrabands henceforth. Instagram introduced systems for liking and following to imitate the actions that trigger dopamine release and form prospective-valued circuits leading to more engagement (Rose-Stockwell, 2023). After the platforms achieved the fifth curve or inflection point on growth rate, the wave of joining the platform became snowballing whether the company had the best product or not. The vital challenge that the bandwagon incumbents meet is the fact that the transition costs for substitutes become very high with growing extent in big networks. 

Disruptors without significant differentiation fail to short-circuit the barriers built in around Facebook/Amazon/Google, which stand in the way of their takeover at their current scale. This creates attractiveness for early starters who presumably gain exponential scaling advantages over the path of innovation through preferential early scaling. However, if left to market forces alone, the lines between more deserving and less innovating develop with such a condition. Locked ins inherently associate the organic competition of legitimacy with true quality. Policies such as data portability modelled by regulators may help introduce flexibility which would loosen oligopolistic structures and hence reduce the friction of switching (Masuch et al., 2018). Interventions to ensure that the free space is allowed for new and innovative alternatives to surface without copying these prematurely, because features and marks need real organic showing.

Deliberately associated with the ideas of herding and bandwagons is the Veblen effects theory that was advanced by the renowned economist Torstein Veblen who was interested in the ostentatious consumption of luxury goods as a means of demonstrating high social status. Platforms engage these psychological buttons by herding customers and their affiliations in common environments that create an impression that certain products/experiences are expected or admired due to this attendance (Hietanen et al., 2018). Strategic seeding of the novel digital offerings, like exclusive virtual clothing or Follower/Like badges on social media, directly impacts the “cool factor” experiences. Humblebragging is a common practice among influencers as they demean products in a pretense of going against societal norms to stir jealousy and such insignificant feelings as acceptance and prestige among their followers (Moran, J., 2020). Cultivated brand association that is because of ad placement cannot happen without some level of status relevancy tied up with being a user of the promoted lifestyles.

By the systems of rewards, the thirst of following the uprating is installed as it is measured by the social proof indicators. By providing public scoreboards and leaderboards, the system motivates people to stretch their abilities beyond their limits to outcompete their rivals as human perception remains in the brains of primal instincts. Through the mechanism of scarcity, limited marketing avenues drives demand for events as unrestricted access is unheard of. Provoking unsatisfied desires avails the granted want keeping people in constant preoccupation with the craving for luxurious cherishing status economies (Heinberg, 2021). Even though the artificial status symbols can give everyone a chance to discover an alternative way of self-expression, it might as well homogenize self-expression only around what the world believes to be attractive, not what the person wants.

1.4 Implications of Network Manipulation 

The network manipulation strategies employed by dominant digital platforms ultimately restrict competition in the market. Through preferential attachment in search rankings and recommendation algorithms that favor their own services, platforms make it difficult for competitors to gain traction and market share. The "rich get richer" dynamics reinforce their positions as entrenched incumbents while raising barriers for new entrants. By acquiring influential players like YouTube and Instagram, platforms also undermine potential competitive threats and consolidate control over entire social networks (Hopp et al., 2018). This limits rivals' access to users and data, crucial resources for innovating in the digital economy. Segmenting networks and restricting interoperability between ecosystems traps users within closed proprietary systems as well, insulating platforms from competitive pressure.

As switching costs rise due to lack of data portability and network effects, user lock-ins are created that hamper their ability to easily migrate to alternative services. This dampens competitive pressures on incumbents to continuously improve and innovate. The resulting market concentration and dominance of a few tech giants reduces the choices available to users over the long run-in terms of price, quality, and privacy standards. Regulatory interventions may be needed to curb anti-competitive effects and open spaces for competitive disruption (Vezzoso, 2021). By strategically manipulating networks, platforms can influence user behaviors and choices in ways that can sometimes compromise user welfare. Herding and bandwagon effects engineered into recommendation algorithms may crowd out niche options and viewpoints that do not gain initial traction (Pontikes and Barnett, 2017). Lack of transparency around how user data is collected, and algorithmic processes defined also reduces user agency.

With barriers to switching erected between closed ecosystems, user choice in terms of which platforms and services they can engage with gets restricted over time. This affects not only their control over personal data and digital profiles but also undermines dynamic competition that grants better deals and tailored experiences from diverse options. Standardizing on several most popular platforms decreases the variety of experiences existing in our digital universe. When platforms manipulate social interaction in a disguised way and then human defenselessness through cognitive biases, there are several ethical issues (Olteanu et al., 2019). Creating consumer psychology on mass scale for a commercial purpose will result in some features like social evidence, status signals and artificial scarcity to the consumer paradise, and thereby is a matter of criticism among people. Through this, a loop of automation between the user, algorithm and recommendation system is created undermining the user`s autonomy and consent over how their preferences are formed online.

The immediate and long-term effect on the behavior and health of individuals may be compromised by herding effects or as jargon or clickbait are amplified to increase visibility. The effect of information distribution without diversity and neutrality is almost certain to alter public discourse as well as the reputation of the democratic process (Koene et al., 2019). Businesses market this as a helping hand that optimizes user experience. Lack of transparency and independent oversight on the part of architecture that gets more powerful over time gives way to corruption and other unintended social harms. It is time for the noticeable ethical and regulatory barriers to be put in place.

1.5 Leveraging Cognitive Biases and Social Phenomena

In addition to network effects, platforms leverage cognitive biases and social phenomena to influence user behavior. They design systems that can unintentionally reinforce echo chambers by filtering information based on past user interactions. There is a tendency for users to primarily engage with others holding similar views. Platforms also tap into conformity bias by showcasing the most popular posts or videos (Figà Talamanca and Arfini, 2022). This encourages users to align their thoughts and actions with the perceived social norms and behaviors of the majority. Another effect exploited is homophily where connections tend to form between similar individuals like people of same gender or occupation (Nedkovski and Guerci, 2021). Networks allow for easy following and connecting with others sharing common attributes.

Centrality measures help identify influential nodes with many connections. Degree and eigenvector centrality are used to find creators with high centrality whose content platforms often promote to shape information flow. The majority illusion can cause individuals to perceive a widely expressed opinion as the view of most, even if it may not be (Jost et al., 2022). Selective curation strategies are used to promote consensus around certain opinions. Double counting of links when measuring centrality can artificially inflate some nodes' importance, allowing potential exploitation by platforms.

Conclusion

This essay has addressed how influential digital platforms strategically utilize network structures and are driven by related social phenomena to gain an advantage over their rivals. Their affinity for acquiring specific nodes, lack of interconnectivity, and higher cases of lock-in and switching costs hamper the long-term nature of market competition. This process of market concentration harms the consumers by threatening their privacy, choice, and accessibility, and eventually, puts their personal data in the hands of the corporations with no sufficient oversight and user empowerment. Ethical considerations are also brought about by arguing that platforms are using human cognition and social cues at a large scale to subtly shape behaviors online and as such more safeguarding measures are required.

Dynamic competition was moved to the forefront in future policies which required creating open passages among fragmented networks and proprietary ecosystems. Data Portability, Interoperability Standards and avoiding the monopolization of information standardization bodies could serve the same purpose. The initial regulations will cover potentially occurring practices like discriminatory treatment of competitors through the platforms. It remains, however, that additional multidisciplinary investigation must be done and more often, practical testing. Networks and digital markets ought to be included in the research agenda to learn long-term looping mechanisms and the cliff points. 

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Appendix

Table 1: Summary of network manipulation strategies discussed in Section 2.2