Loading...
This study examines how Kremlin-compatible narratives can acquire additional credibility when they are reproduced by genuine Western LinkedIn users whose profiles signal professional expertise, institutional experience or specialist knowledge. The analysis began with recurring comments beneath the author's LinkedIn posts and was expanded to the users' own posts, reposts and activity beneath the pages of public officials, institutions, media outlets and analysts. The final sample covers ten anonymised public profiles from several Western countries and professional sectors. The study does not claim that these users are controlled, paid or directed by the Russian state. Instead, it analyses observable content, repetition, source selection, distribution behaviour and political effect. Across the sample, recurring narrative clusters include claims that NATO or the United States provoked the war, that Ukraine functions primarily as a Western proxy, that Ukrainian victory is impossible, that military assistance merely prolongs the conflict, and that territorial concessions should be treated as pragmatic peace. Three mechanisms are especially visible: audience piggybacking through comments beneath high-visibility pages, source amplification through a recurring ecosystem of Western commentators, and professional legitimisation, in which status cues make familiar narratives appear more independent or authoritative. The findings suggest that the strategic significance of such activity lies less in producing overt support for Russia than in normalising doubt about assistance to Ukraine and increasing the political cost of sustaining it.
Keywords: LinkedIn; Russia; Ukraine; information influence; FIMI; narrative amplification; OSINT; professional credibility; social media; strategic communication
Key finding: The study does not identify a coordinated Russian network among the ten profiles. It identifies a recurring process in which narratives compatible with Kremlin strategic messaging are translated into Western political language, circulated by genuine users, and given additional credibility by the professional context of LinkedIn.
Russian information influence in Western digital environments is often discussed through the most visible instruments: anonymous accounts, fabricated media brands, coordinated troll activity and covert influence operations. Those mechanisms matter, but they do not describe the whole problem. A narrative can continue to circulate after it has left the infrastructure that originally produced or amplified it. It can be repeated by genuine users, adapted to local political language and presented as independent analysis, realism, anti-war commentary or professional judgement.
LinkedIn is a particularly useful environment in which to examine this process. Unlike platforms built primarily around entertainment, personal networks or rapid political commentary, LinkedIn organises trust around professional identity. Job titles, academic qualifications, institutional affiliations, sectoral experience and visible professional networks are integral parts of the message environment. They do not prove expertise on a given subject, but they influence how other users interpret what is being said.
The starting point for this research was a recurring pattern beneath the author's own LinkedIn posts. Whatever the immediate topic - a Russian strike, Belarus's role in the war, military assistance, mobilisation or European security - discussion repeatedly returned to a relatively stable set of explanations. Russia's agency was moved into the background, while NATO expansion, the United States, Ukrainian corruption, mobilisation, the presence of Ukrainian men abroad or the alleged futility of military support were moved to the centre.
Comments alone were insufficient for broader conclusions. The analysis therefore moved outward from individual interactions to the public activity of the users themselves: their original posts, reposts, recurring sources, repeated interventions beneath institutional pages and the ways in which the same causal explanations were carried into different discussions.
The central research question is: how do genuine Western LinkedIn users contribute to the legitimisation and diffusion of Kremlin-compatible narratives within professional online environments? The term "Kremlin-compatible" is used deliberately. It refers to claims whose causal framing or policy implication overlaps with recurring Russian strategic messaging. It does not mean that the speaker is a Russian agent, that the content originated in Russia, or that the user acts with conscious intent to assist the Kremlin.
Information influence should not be assessed only by vocabulary. A message can change its wording while preserving its political function. "Denazification" may disappear and be replaced by a "security dilemma". A Russian ultimatum may be reframed as a "peace proposal". Restricting Ukraine's military capacity may be described as "de-escalation". Acceptance of territorial conquest may be presented as "pragmatism". The rhetorical register changes, but the policy implication can remain broadly favourable to Moscow.
For this study, the relevant question is therefore not whether a user repeats an official Russian slogan word for word. The question is whether the combined explanation of the war systematically shifts responsibility away from Russia, reduces Ukrainian political agency, presents Western assistance as irrational or dangerous, and normalises outcomes that reward the use of force.
Professional legitimisation describes the additional credibility that a claim can acquire from the social setting in which it appears. On LinkedIn, a statement is encountered beside a professional biography. A management consultant, lawyer, engineer, intelligence analyst, educator, entrepreneur or civil-society figure is not necessarily an expert on Russia or Ukraine, but the structure of the platform encourages audiences to read political commentary through the lens of professional status.
This creates an important distinction between message origin and message reception. A claim that would immediately be recognised as partisan or propagandistic under a state-media label may be interpreted differently when it is reproduced by a genuine person under their own name, surrounded by markers of professional credibility. The study treats that credibility effect as an analytical mechanism rather than as evidence of the truth or falsity of any individual claim.
The study uses purposive qualitative sampling. Profiles were not selected because they criticised NATO, supported negotiations or expressed an unpopular political opinion. The core inclusion criterion was repetition: did the same user return to substantially the same causal explanation of the war across multiple discussions, repeatedly draw on a similar source environment, or distribute the same policy conclusion under different high-visibility pages?
The original working dataset contained 28 publicly available episodes linked to nine LinkedIn profiles. During finalisation, one additional profile was screened using the same criteria and included after repeated activity was identified; four additional episodes from that profile were coded. An episode was defined as an original post, repost or comment in which one of the narratives under examination was repeated or a corresponding source was actively distributed.
In parallel, 217 comments beneath three of the author's LinkedIn posts were reviewed as a screening pool. Eight comments were retained for close reading because they directly repeated historical, political or security explanations whose practical conclusion was to weaken trust in Ukraine, shift responsibility for the war onto the West, or normalise concessions to Russia.
The sample is not representative of LinkedIn as a whole. It is a pilot study designed to identify recurring mechanisms and generate hypotheses for larger-scale research.
All analysed profiles were publicly accessible and belonged to identifiable users. In the published version, however, they are anonymised as P1-P10. Country and professional sector are retained in broad form because both are analytically relevant to the study's central question. Exact employers, profile URLs and uniquely identifying job titles are omitted. The underlying archive of public posts and comments is retained by the researcher for verification and follow-up research.
This decision is not intended to imply wrongdoing. The unit of analysis is the pattern of public communication, not the personal identity of the user. Anonymisation also helps prevent the paper from being read as a list of alleged "agents" or "propagandists", a conclusion the evidence does not support.
Episodes were coded for five dimensions:
Open-source data cannot establish payment, hidden contacts, state direction or the subjective intent of individual users. The study therefore does not determine who acts knowingly, who is guided by personal political convictions, or who simply reproduces arguments absorbed from a narrow information environment. It also does not classify the ten profiles themselves as FIMI actors. The analysis is limited to observable content, behaviour, source use and political effect.
Across the sample, the same broad causal chain appears in different forms. NATO or the United States is presented as having provoked Russia; Ukraine is depicted as an instrument of Washington rather than as an independent actor; the 2022 negotiations are described as an almost completed peace settlement blocked by Western governments; and Russian policy is reframed as a defensive response to external pressure. The next step is usually a claim about inevitability: Ukraine cannot win, continued resistance only increases casualties, and Western weapons merely prolong a war whose outcome is already decided.
Each proposition can be discussed separately. The analytical significance lies in their combination. Together they create a closed explanatory system in which Russia's decision to invade becomes secondary, Ukrainian agency is reduced, and responsibility is transferred to NATO, Washington or Kyiv. The preferred policy outcome follows naturally from the frame: reduce military support, pressure Ukraine to compromise, or accept Russian territorial control as the price of peace.
Legitimate concerns are often incorporated into this chain. Corruption in Ukraine, mobilisation practices, the financial burden of aid, Western weapons shortages and escalation risks are all valid subjects for scrutiny. Within the sampled episodes, however, these issues frequently function not as independent objects of analysis but as bridges to the same conclusion: supporting Ukraine is futile, excessively costly or morally suspect.
The ten profiles are presented below as behavioural case studies. The descriptions intentionally avoid claims about motive, affiliation or hidden coordination. They focus on what is publicly observable: repetition, framing, source use and distribution method.
P1 demonstrates the clearest form of audience piggybacking. Across posts by senior European officials, major analysts and a British defence institution, the profile repeatedly described Ukraine as a "disposable pawn", characterised the war as a US or NATO proxy conflict and invoked regime change in Kyiv as part of the causal explanation. The same profile also used its own posts to circulate material from commentators who attribute the invasion primarily to NATO and US policy. One comment beneath a British defence-related post attracted more than two hundred visible reactions. Reactions are not equivalent to endorsement, but the episode shows how a persistent commenter can enter a large, pre-existing audience without building a media platform of their own.
P2 illustrates a fixed causal frame applied across changing subjects. In separate discussions, Ukraine was described as an "artificial state", as the result of a US-funded political intervention and as the party responsible for provoking the conflict by rejecting Russian requirements. Peace was linked to NATO withdrawal from Russia's borders. The opening topic changed, but the explanatory structure remained stable: Russia was framed as reacting to Western or Ukrainian actions rather than as the state that chose to launch a full-scale invasion.
P3 represents an original-content model rather than a primarily comment-based one. Through an independent media and commentary channel, the profile repeatedly framed the war as a NATO proxy conflict, presented Ukraine as an instrument of Western power and emphasised the risk that Ukrainian strikes on Russian strategic targets could trigger nuclear escalation. The rhetoric is recognisably Western and anti-establishment: American imperialism, anti-war politics, legal criticism and nuclear risk. This matters because the political logic can travel further when it no longer resembles an overt Russian state-media product.
P4 demonstrates repeated self-promotion across professional discussions. The profile inserted its own concept of "peaceful coexistence" with Russia beneath pages dealing with economics, policy and European security, often presenting the conflict as a confrontation between NATO and Russia "in Ukraine" rather than as Russian aggression against Ukraine. The same article or conceptual framework was repeatedly used as an answer to different discussions. The distribution technique is important: rather than relying on a single viral post, the user repeatedly places a pre-existing interpretive framework into new professional audiences.
P5 is especially relevant to professional legitimisation. The profile publicly presents itself through the vocabulary of intelligence, OSINT, SOCMINT, cognitive warfare and strategic research. In material on Ukraine, the war is described as already lost, framed as a proxy confrontation between Russia and the United States, and attributed heavily to "Anglo-American" policy. References to well-known Western thinkers provide additional intellectual framing. The point is not that professional terminology invalidates or validates the argument. It is that LinkedIn places the claim beside an expert identity, which can alter how an audience evaluates its authority.
P6 is a source-amplification case. Rather than constructing a detailed original argument, the profile circulated material claiming that NATO provoked Russia and undermined the peace process. This illustrates a lower-effort but potentially effective dissemination model: the user lends their own professional identity and network to a narrative produced elsewhere. Repetition across users can make a narrow source ecosystem appear broader and more socially distributed than it actually is.
P7 likewise functions through recommendation. The profile directed its audience to a commentator presented as explaining how the war began, who "really started" it and why it would continue or escalate. The significance lies in source delegation: instead of reproducing every claim, the user certifies a source as the interpretive key to the conflict. In network terms, recommendation is itself a form of amplification because it transfers both attention and credibility.
P8 amplified a long-form interpretation centred on American responsibility, NATO expansion, Ukrainian neutrality and the claim that the war could have been avoided if the West had accepted Russian security demands. The post incorporated the material into a broader critique of US decline and argued that neutrality better served national interests. This case shows how a Ukraine-related narrative can be embedded within an existing ideological worldview and adapted to a domestic policy debate far from Europe.
P9 illustrates source aggregation. The profile repeatedly brought material from a small group of commentators into LinkedIn discussions and presented the conflict as a direct confrontation between the United States, NATO and Russia. Here, the analytical value lies less in any single post than in the cumulative source pattern. A user who repeatedly republishes the same interpretive ecosystem can function as a distribution node even without evidence of formal coordination.
P10 was added during finalisation because the profile displayed repeated activity matching the existing inclusion criteria. In one post, the profile stated that the conflict in Ukraine had been "provoked" while responding to a discussion of European defence procurement from the United States. In another, it challenged an HCSS assessment of Russian sub-threshold activity, questioned attribution of reported drone incursions and criticised the absence of a diplomatic pathway with Russia. Elsewhere, the profile rejected the term "shadow fleet" as one-sided rhetoric, defended sanctions evasion as economic self-protection and repeatedly framed European security policy as subordination to US hegemony. The profile also circulated material arguing that NATO enlargement crossed Russian red lines. Across these episodes, the details change but the causal frame remains consistent: Western policy is treated as the primary driver of escalation, while Russian actions are interpreted mainly as reactions to external pressure.
The most platform-specific mechanism is the use of other people's audiences. A user does not need a large publication or a substantial follower base if the target audience has already been assembled by a government institution, public official, think tank or well-known analyst. Repeated commenting allows a narrative to attach itself to high-visibility discussions and to benefit from the legitimacy of the institutional setting in which it appears.
This does not mean the institution endorses the comment. The mechanism is distributional, not institutional. The value comes from visibility, proximity to authoritative content and the possibility that repeated interventions create the impression of broader consensus.
The material rarely relies on overtly Russian terminology. Instead, it is translated into concepts already familiar in Western debate: realism, anti-imperialism, peaceful coexistence, restraint, neutrality, sovereignty, fiscal responsibility and escalation management. The language is not inherently illegitimate. The analytical issue is the recurring direction of the causal chain and the consistency of the policy outcome.
The publicly available activity of the ten profiles did not reveal a stable system of reciprocal reposting, regular mutual commenting or an observable division of target pages. LinkedIn's limited public visibility means that hidden contact cannot be ruled out, but the available evidence does not justify describing the sample as a single controlled network.
The more defensible connection exists at the level of sources. Across the sample, users repeatedly drew on a relatively narrow circle of Western commentators including Aaron Maté, Max Blumenthal, Jeffrey Sachs, Glenn Diesen, Ray McGovern, Scott Ritter, Judge Napolitano and John Mearsheimer. Reading or citing any of these figures is not evidence of a relationship with Russia. What matters here is the function their material performs inside the sample: it provides Western authorship for explanations centred on NATO provocation, diminished Ukrainian agency, the impossibility of victory, escalation risk and the need for accommodation with Moscow.
Across sectors, professional status works as a trust multiplier. The strongest version is visible in P5, where intelligence and OSINT terminology directly frames the political argument. But the same mechanism can operate more subtly for consultants, lawyers, engineers, educators, entrepreneurs and civil-society figures. LinkedIn encourages users to interpret content through biography. Expertise in one domain can spill over into perceived authority in another, even when the profile provides no evidence of specialist competence on Russia, Ukraine or military affairs.
The most important effect is not necessarily positive sentiment towards Russia. A user can dislike the Kremlin, criticise Vladimir Putin or reject Russian domestic politics while still circulating an explanation whose practical result is favourable to Moscow. From an influence perspective, creating admiration for Russia is often unnecessary. It may be enough to raise the political cost of supporting Ukraine, to make assistance appear futile, corrupt, escalatory or economically self-destructive, and to transform every new aid decision into a fresh legitimacy crisis.
The sample itself does not establish a direct route from a Russian state structure to any of the ten users. It is nevertheless important to place the findings within the documented information environment in which narratives about Ukraine circulate.
In September 2024, the US Department of Justice announced the seizure of 32 internet domains used in the Russian government-directed influence campaign commonly known as Doppelganger. The operation impersonated legitimate media organisations and sought to influence foreign audiences, including by reducing international support for Ukraine.
France's VIGINUM documented the Portal Kombat ecosystem, a structured network of pro-Russian information portals that republished and localised content for audiences across multiple countries. Its investigations described a system designed primarily for mass distribution rather than original reporting.
Meta's threat reporting on Cyber Front Z described a St Petersburg-linked troll operation that targeted multiple online services and attempted to manufacture an appearance of grassroots support for Russia's war. Meta noted that the operation extended beyond its own platforms and targeted services including LinkedIn.
In June 2026, the European External Action Service and Ukraine's Centre for Countering Disinformation published a joint analysis of Russian FIMI targeting Ukraine's path towards EU membership. The study recorded approximately 244,000 publications generating 1.39 billion views between January 2025 and April 2026 and highlighted mass content production, cross-platform amplification and information laundering.
These investigations do not prove that the ten LinkedIn profiles studied here participated in any of those operations. They establish something narrower but important: Russia and Russian-linked actors have repeatedly invested in systems that produce, disguise, localise and amplify political narratives across Western information environments. The LinkedIn cases examined in this paper represent a separate downstream phenomenon: compatible explanations can be reproduced by genuine users without any demonstrated command relationship.
The evidence supports several interpretive hypotheses, not conclusions about individual psychology. First, some narratives fit pre-existing scepticism of US foreign policy. Iraq, Afghanistan and Libya provide a ready historical frame through which later conflicts are interpreted. When that frame becomes universal, however, a critical distinction can disappear: the difference between a war initiated by the United States and a war in which the United States supports a country attacked by another state.
Second, fear of escalation creates an asymmetry of political pressure. The actor making nuclear threats may acquire leverage precisely because others fear the consequences of resistance. Under this logic, restraint is demanded from the party with fewer escalation options, while the threat itself becomes the reason to limit assistance to the threatened state.
Third, symmetrical explanations are psychologically and politically attractive because they make a complex war look like a clash of two blocs rather than an asymmetric act of aggression. "Both sides", "great-power rivalry" and "security dilemma" frames can sound balanced even when they distribute agency unevenly.
Finally, LinkedIn adds a platform-specific incentive: professional self-presentation. Users are rewarded socially for appearing informed, independent and analytically sophisticated. A contrarian position can signal intellectual autonomy. When combined with a polished professional profile, that signal can become persuasive even without strong evidence.
An information operation does not need to reverse public opinion completely. Delay can be strategically valuable. Reducing the size of an aid package, slowing a procurement decision, increasing parliamentary resistance or making political leaders expend more capital to defend support can all produce material effects.
For that reason, the relevant indicator is not simply whether Western audiences "support Russia". A more useful question is whether repeated narratives make support for Ukraine harder to sustain at the moment when such support can still affect battlefield conditions, deterrence or negotiating leverage.
This pilot study has several limitations that should constrain interpretation.
These limitations are not incidental. They define the appropriate level of inference. The paper identifies a communication mechanism and a recurring narrative pattern; it does not identify a covert organisation.
This study began with a simple observation: arguments beneath unrelated LinkedIn posts repeatedly converged on the same explanation of Russia's war against Ukraine. Expanding the analysis beyond the comments revealed that the pattern was not confined to isolated exchanges. Across ten public profiles, similar narratives were carried through different professional identities, source ecosystems and distribution techniques.
The most important finding is not that every profile says the same thing. They do not. Nor is there evidence that they form a coordinated Russian network. The commonality lies in political function. Russia's responsibility is repeatedly relativised, Ukraine's agency is reduced, Western support is framed as futile or dangerous, and concessions to the aggressor are normalised as realism or peace.
LinkedIn adds a distinctive layer to this process because professional identity is part of the communication itself. A claim does not arrive alone; it arrives beside a biography, title, company, qualification or expert label. That context can turn familiar narratives into apparently independent professional judgement.
Direct control over every amplifier is therefore unnecessary for a narrative to achieve strategic value. Once an explanation is adapted to Western political language and embedded in existing anxieties about war, public spending, US power, corruption or escalation, genuine users can reproduce it for their own reasons. The result is not necessarily mass sympathy for Russia. More often, it is erosion: more doubt, higher political cost, slower decisions and a growing sense that sustained assistance to Ukraine is unreasonable or impossible.
Future research should test this mechanism on a larger dataset, compare LinkedIn with X, Facebook and YouTube, measure temporal repetition, map source pathways and use multiple coders. The central research challenge is no longer only to identify where propaganda begins. It is to understand what happens after a narrative has been translated, detached from its origin and reintroduced into a professional environment as ordinary independent opinion.
English
Українська