Abstract
LinkedIn is the world’s largest online professional network where users can post content to achieve professional goals and convey a professional presence online. Most academic studies about LinkedIn overlook the content of these posts. Therefore, this study systematically analyzes what topics LinkedIn users post about and identifies the content that garners the most engagement. Upon conducting a thematic analysis and nonparametric tests of 1,001 users’ posts, this study categorized each post into five main themes: Business, Personal, Expertise, Interpersonal, and Observances. While Business posts were found to be the most frequent, Interpersonal and Observance posts generate more comments and reactions comparatively. Meanwhile, Business and Expertise posts get reposted more frequently. These findings provide empirical evidence of what users talk about on the platform, which enables further academic study of how users leverage the platform to achieve their professional goals and convey a professional presence to their networks. They also provide practical implications for users seeking to maximize their engagement and outcomes on the platform.
Introduction
LinkedIn (2024) is the world’s largest professional networking platform that connects over a billion users globally. Unlike Facebook, Instagram, and X, LinkedIn offers professionals a digital space to build their networks, seek employment, and establish an online professional presence. Users can also share career milestones, industry insights, and personal reflections through posts that appear in their connections’ feeds when they log in. LinkedIn (2024) claims that over 1.6 million feed updates are viewed per minute.
Despite the frequency and prominence of posting on LinkedIn’s feed, there is a lack of scholarly research about the nature of these posts from individual users and their engagement metrics. While LinkedIn researchers have investigated posts from business accounts aiming to sell a product or service, such insights lack relevance to individual users seeking to advance their careers. This gap is significant because professionals use LinkedIn for the purpose of career growth (Pena et al., 2022) and career benefits are associated with active use (Cho & Lam, 2020; Davis et al., 2020). University career centers embrace LinkedIn as a career tool (Osborn & LoFrisco, 2012), and educators from various fields teach it in their professional development classes (Cooper & Naatus, 2014; Hutchins, 2016; López-Carril et al., 2025). Finding out what kind of content gets posted and what yields engagement is essential for understanding LinkedIn as a unique social media platform. Moreover, such insights can enable users to optimize their posts, expand their reach, grow their networks, and unlock new professional opportunities (Healy et al., 2023).
Thus, our study’s objectives are to analyze what individual users post on LinkedIn and identify which topics yield the highest engagement regarding reactions, comments, and reposts. The implications of our study are three-fold. First, social media researchers can deepen their understanding of LinkedIn’s unique user-to-user communication dynamics compared to non-professional social media sites. Second, educators can equip students with insights to foster consistent, engaging posting habits. Third, individual users can refine their posting strategies to enhance their professional visibility and success on the platform.
Literature Review
There has been a growing body of research on LinkedIn that has explored various aspects of its use as a professional networking platform. Studies have examined user motivations, such as those outlined by Uses & Gratifications (U&G) theory, which explains why individuals engage with media to fulfill specific needs (Smith & Watkins, 2023; Utz, 2016). Other studies have focused on the structure and content of LinkedIn profiles, such as their influence on hiring potential, personality assessments, and professional branding (Altenburger et al., 2017; Fernandez et al., 2021). Research has also explored how organizations and executives use the platform for marketing, corporate social responsibility, and professional relationship building (Mora Cortez et al., 2023; Pérez-Serrano et al., 2020). Additionally, some studies have analyzed engagement patterns on LinkedIn and other social media platforms, identifying factors such as post timing, content type, and interactivity that influence user responses (Singh et al., 2023).
Despite these advancements, there is limited research on the posting behaviors of individual LinkedIn users and their associated engagement metrics. To show this gap, we synthesize the current LinkedIn literature into four key areas: (1) uses & gratifications (2) LinkedIn profile content, (3) the role of LinkedIn in business marketing, and (4) engagement patterns on LinkedIn compared to other platforms. By examining these areas, we provide a foundation for understanding the unique contributions of our study to understanding LinkedIn and human behavior.
Uses and Gratifications
According to Uses and Gratifications (U&G) theory (Katz et al., 1973), users are motivated to engage with media based on specific gratifications that they seek to fulfill. The theory posits that there are five different types of needs that users have: cognitive, affective, personal identity, social integration, and escapism. In the case of LinkedIn, a self-purported professional network, one might posit that individuals use the platform for personal identity needs; the desire to convey status, gain credibility, and advance their professional agendas via self-promotion. Indeed, Smith and Watkins (2023) found in their surveys that millennials use LinkedIn to find information, communicate their professional achievements, and monitor their peers. Other studies on gratifications have investigated professors’ platform segregation with LinkedIn (LaPoe et al., 2017), perceived informational benefits (Utz, 2016), student adoption of the platform (Hazzam, et al., 2025), outcome expectations (Pena et al., 2022), uses for architects and designers (Sauer et al., 2024), and self-selection into joining the network (Brenner et al., 2020).
While these U&G studies focus on self-reported user motivations, we seek to provide a behavioral insight into users’ purposes of using LinkedIn by studying what they do on the platform in terms of posting and reacting to other posts.
Profiles
Outside of uses and gratifications, many studies focus on LinkedIn profiles. Profiles are found to be crucial to new graduates’ success on the platform and in their careers (Sauer et al., 2024). Some studies investigate the profile summary structure (Bremner & Phung, 2015), argument quality (Chiang & Suen, 2015), and gender differences in the writing (Altenberger et al., 2017; Moore, 2019). Other research has found that profile content positively correlates with specific job performance metrics (Aguado et al., 2019), hiring potential (Harrison et al., 2024), personality traits (Fernandez et al., 2021), and even the truth about one’s work experience (Guillory & Hancock, 2012). Profiles also display the user’s connection counts and researchers have investigated the effects of these counts on entrepreneurial fundraising (Banerji & Reimer, 2019) and favorability (Roulin & Stronach, 2022).
LinkedIn profile pages also display the user’s most recent post activity. However, none of these studies investigate the content of LinkedIn posts, resulting in an incomplete understanding of user activity and profile display.
Business Marketing Accounts
Thus, while gratifications and profile construction matter, LinkedIn is a social network where people communicate via posts and private messaging. When posts are studied, it is often of business accounts (Brewer & Imes, 2023; Mora Cortez & Ghosh Dastidar, 2022; Mora Cortez et al., 2023; Sundström et al., 2021). Two studies on individual user accounts investigate posts about medical topics, such as the disclosure of urticaria (Mondal et al., 2024) and mental health problems (McChesney & Foster, 2024). Outside of medical topics, there has been one study of what the Ibex 35 CEOs post on their individual LinkedIn accounts. Pérez-Serrano et al. (2020) found that most CEOs post infrequently and that only 13.3% have active profiles. Most posts prioritized corporate communication themes such as corporate social responsibility, business performance, product updates, and corporate events. Personal branding topics in CEO posts were far less frequent and encompassed professional achievements, social cause support, and personal interests like sports or hobbies. There have been no studies of any population segment other than these high-level CEOs.
Engagement on Other Platforms
In addition to understanding what topics users post on LinkedIn, we should also learn what content garners the most engagement. Shields (2017) defines engagement as actions a user takes in response to content such as liking, commenting, clicking, and sharing. We measured engagement by the number of reactions, comments, and reposts. Shields (2017) argues that these metrics are a “truer measure of familiarity than reach and impressions” (p. 178) and that users choosing to interact with content is a stronger indicator of impact. There are many studies about engagement on other social media platforms including Facebook, X, and Instagram. Some investigate the use of pictures, videos, and weblinks in posts and their impacts on engagement (Berbegal-Mirabent & Caballero, 2023; Gutiérrez-Cillán et al., 2017; L.-C. Huang & Chen, 2018; Iqbal Khan & Ahmad, 2022; Romero-Jara et al., 2024; Torbarina et al., 2020; Wang, 2023). Outside of media, other studies have found that one’s level of interactivity (Marino et al., 2022), the timing of a post (Singh et al., 2023), and perceived usefulness (Gutiérrez-Cillán et al., 2017) are all factors influencing engagement on Facebook, X, and Instagram.
There have been only a few studies about engagement on LinkedIn and they all focus on business accounts. L. Huang et al. (2019) found that infographic posts on LinkedIn and X about community sustainability plans received the highest engagement compared to ones written in an academic or public information style. Mora Cortez and Ghosh Dastidar (2022) studied a Chilean-Swiss consultancy firm’s LinkedIn activity and found that their marketing posts that were perceived as “exciting” led to more likes and posts perceived as “competent” generated more clicks.
There have yet to be studies that have investigated a wider range of post topics from individual users. Moreover, given that many studies on other social media sites complement and also contradict each other, our study can add clarity regarding LinkedIn as platform in the cross-platform discussions.
Research Methodology
Research Questions
If LinkedIn is a site for professionals across various stages in their careers, there ought to be a study of posts from a random sample of individual users that can give a broader understanding of the communication that happens on LinkedIn. Our study aims to explore what a random selection of individual users posts on LinkedIn instead of business marketing accounts. Therefore, we pose the following qualitative question:
We also want to know which topics get the most engagement. It is one thing to post a particular topic; it is another to attract reactions, comments, and reposts (all collectively known as “engagement”). By knowing which topics get the most engagement, we can learn more about what topics garner interest from viewers. Hence the quantitative question:
These two driving questions enable us to understand what topics people post, their frequencies, and how effective they are.
Data Collection
We needed to acquire LinkedIn posts and their engagement metrics to answer our questions about what users post on LinkedIn and what gets the most engagement. LinkedIn offers no central directory that enables a researcher to select users randomly from a list. All researchers must enter search terms outside of what appears in their feed to begin accessing content outside of their network. Thus, we entered search terms including “Dallas,”“Fort Worth,” and “Dallas Fort Worth” in the search box. These searches brought a list of profiles with those terms in their location or job title. We used these search terms because they were neutral toward any job or industry. Moreover, the Dallas Fort Worth metroplex is the fourth largest metroplex in population with the fourth largest concentration of Fortune 500 copies in the United States, which makes it naturally diverse in terms of industries and demographics (Khan & Rapp, 2022). We then clicked on the profiles that appeared under “People” in the search results to filter out company accounts and group pages matching those search terms.
When we accessed the profiles, we manually extracted the user’s most recent public post with the number of reactions, comments, and reposts. We chose these metrics since they are immediately accessible and are commonly used in the previously mentioned studies on engagement. We only collected one post per user to ensure sample diversity among differing user activity levels and it was always their most recent one. Not every profile that we visited had a post. We had to view 1,493 profiles to reach our sample size of 1,001 posts. That means 34% of LinkedIn users in our initial sampling have never posted. We also tracked whether a post was original (written by the user) or a repost of another user’s post. Of the 1,001 posts, 430 (43%) were reposts.
LinkedIn does not natively provide precise timestamps for posts, especially older ones. To determine the post’s age, we used a LinkedIn post date extractor website to get its exact day and time (Fox, n.d.). We then subtracted the current date from the post date to get a day count for the post’s age. The average post’s age in our sample was 499 days. We extracted posts between January and June of 2024. We stopped at 1,001 posts due to the time and resource constraints associated with manually recording each post and because LinkedIn has limits for the number of profiles one can visit per day.
Analysis
Once all posts were collected, the lead researcher initially coded all posts using ATLAS.ti. This initial open coding enabled familiarization with the post content and laid a foundation for the team to build a comprehensive coding scheme. The researcher developed a prototypical codebook for classifying post topics. This initial codebook had 9 categories and 50 subcategories.
Once the lead researcher developed the initial coding scheme, they enlisted two other coders to validate, train, and continuously revise the codebook. We reached a Cohen’s Kappa of .81 after training with 100 posts and revising the initial codebook 6 times, which exceeds the minimum 0.60 threshold for adequate agreement (McHugh, 2012). We then proceeded to code the remaining 991 posts. As we coded the remaining 991, we revised the codebook three more times and adjusted prior codes accordingly during weekly check-in meetings.
Each post was assigned one code. However, there were 74 posts that could fit multiple categories. To address this, we weighed specific categories to take precedence over others if both were present. For example, if a post had professional advice and a call-to-action to buy a service, we gave precedence to the call-to-action. If a post had gratitude with tags and a personal announcement, then gratitude received precedence. The order of precedence was based on what we perceived to be the poster’s primary intention. The order was: Business > Gratitude > Personal > Expertise > Observances.
After coding all posts and counting their frequencies, we streamlined our codebook by combining infrequent categories with larger ones via reclassification. If a code did not occur at least 10 times (1% of the sample), we combined it with another. The final coding scheme ended with 5 categories and 19 topics.
Once we coded all posts and simplified the scheme, we used Microsoft Excel 365 and Tableau 2022.1 to conduct frequency counts on all categories and subcategories. We analyzed the engagement metrics by calculating the mean, median, and standard deviation for each category and code, which included the number of reactions, comments, and reposts. Since there were different frequency counts for each category, we ran non-parametric statistical tests in SPSS to determine whether there were any statistically significant differences between the categories. This analysis helped us determine if certain categories garner more engagement than others.
Our descriptive analysis showed a few outliers in engagement. For example, the top-performing post garnered 128,209 reactions, which created a range of 128,209 since some posts had 0 reactions. To deal with outliers, we eliminated the top 1% of posts in reactions from the analysis under the presumption that a small percentage of posts in a large sample will go viral or have unusually high engagement. We chose 1% as the smallest whole percentage, maintaining the large sample size. Eliminating these 10 posts reduced the range from 128,209 to 12,230 (1.02 orders of magnitude) and the sample size to 991 posts.
Findings
What Topics Do People Post About on LinkedIn?
To answer our first Research Question, our analysis created the following 5 categories with 19 subcategories. The table with each code and its description is displayed in Table 1.
Coding Categories and Sub-Categories with Descriptions and Frequencies.
Overall, users post about a wide range of topics on LinkedIn. We also ordered the sub-categories from the most to least frequent in Table 2 for a simplified view.
Frequency Counts of Each Sub-Category From Most to Least.
Outside of the top five, the next closest topic was Appreciation at 60. The top five sub-categories account for 63% of the sample. Users categorically post about their businesses, careers, professional advice, relationships with others, and social causes. Specifically, the most frequent posts promote a business product or service, offer professional insights, share a job posting, update about a person’s career, or provide a news update about a business. We will elaborate on each of the categories and subcategories in the following sections.
Business
Our first largest category was Business posts, which relate to topics concerning one’s own or another person’s company. There were five common topics in this category that will we discuss.
First, many posts advertise a company’s product or services. These posts include a call to action to purchase something. Users use the platform to promote their products and services and those of others. If we break this topic down further, 92% of posts were about the user’s own company’s products, while 8% promoted another company’s.
Second, users share job openings at their company with posts that often directly linked to the job posting. Users also promoted job openings at companies where they did not work. According to our data, 80% of job opening posts were for one’s own company, while 20% were for another company.
Third, users post updates about their company. These updates cover a range of topics, such as a company’s plan for expansion, acquisitions, company awards, or something that does not directly promote a product or service. We also found that users post updates about their company (85%) and companies they do not work for (15%).
Along with posting about their company’s latest successes, users also share about company events on LinkedIn. They sometimes discuss past events, such as a recently attended company retreat. Users also promote future events like job fairs appearances, educational seminars, and networking events. These posts often encourage other users to attend. In fact, 77% of the posts in this category promote future events.
Lastly, many posts celebrated a company’s work culture. Users write about something they enjoy about their company’s culture without specifically advertising any job openings. For example, users might talk about their company’s embracing of diversity, work life balance, or ways the company makes their job rewarding. Overall, these posts focus on celebrating working with a team and being part of a company.
Personal
Our second largest category is Personal posts related to the user’s career and interests. This category is best aligned with U&G theory’s personal identity needs. Career updates were the most common in this category. Posts in this category often state, “I’m happy to share that I’m starting a new position at [Company]!” LinkedIn is a social network, so users may be inclined to update their network about their latest promotions, job changes, or loss of employment. We included educational achievements and certifications in this category as well. Around 33% of posts were about educational achievements (degrees, certifications), while the rest were about career updates.
Personal interest posts included topics that we deemed to be related to one’s non-professional life, such as religion, politics, family, and sports. Some complexity occurs when a user’s profession is in politics or religion, such as a local mayor or clergy. We classified their posts as company related.
Users also use LinkedIn to make requests. For example, one user posted how they were looking for suggestions for daycare providers close to their work. These posts ask for something that benefits the user individually, such as a network contact, advice, or job leads. Common personal requests were for job leads (e.g., “know anyone hiring?”) and service suggestions (“know a good attorney?”). If the request is for the reader to purchase a product or service, then we considered it a business post.
Users also post reflections on LinkedIn which discuss an overall experience beyond one event. For example, a first-year medical student wrote about how they adjusted to their first semester and the mental challenges he faced, and how is he happy that he overcame them and looks forward to this second year. These posts emphasize what one learned from an experience. They are distinguished from company and industry event posts by their tendency to reflect on a past event and how it benefited them personally rather than promoting a future event or a past event to promote a company.
Finally, LinkedIn users share personal productivity and professional milestones. An example post said, “Another year of success” with a picture of two certificates for meeting sales quotas. Besides personal award announcements, users post about their daily productivity such as completing a long meeting or finishing a training.
Expertise
Our third largest category was Expertise posts, which involved the user showcasing their knowledge of their craft or industry. These posts include professional insights, industry events, and creative works.
Users sharing professional insights is the most common post in this category. These posts often involved the user sharing news articles and media about their industry or profession. Users often stated a reason for sharing the article while giving the link to it. Other times, the user would offer direct advice in their post without any accompanying media. We did not systematically classify the advice topics, but they spanned many areas such as emotional intelligence, effective leadership, legal tips, and homebuying to list a few.
We included updates about industry events in this category, such as promoting a conference or networking event. Users often did this by announcing that they would be attending a specific event. Industry events differ from company events because they are for networking and professional development rather than promoting a company culture or products. Showing that one is up to date on the industry’s latest events implicitly shows one’s expertise and relevance.
Lastly, if the user shared an article or publication authored by themselves, we also considered that a professional insight. For example, a user might post about their new book or article that recently appeared in a newspaper. We also considered promoting one’s own media appearances under this category. If a user promoted their own appearance on someone else’s podcast, for example, we put it in this category.
Interpersonal
Our fourth category, Interpersonal posts, involves congratulating or appreciating another person or set of persons.
Users often appreciate one another on LinkedIn. Many gratitude posts involved the user tagging another user or set of users and explaining why they were grateful. Often, the post included a career update or personal milestone with expressed gratitude toward a tagged or specifically identified user. However, if the post included a career update followed by a generalized “thank you” with no one specifically mentioned, for example, then we counted it as a career update per our precedence rules.
Congratulatory posts involve a user celebrating another person’s achievement. Users might highlight another person’s professional milestone or career update with the goal of praising them. In any case, these posts were about celebrating others rather than oneself.
We also included posts about meeting or spending time with someone at an event. Users might mention meeting some for the very first time at a conference or reuniting with a former colleague. Other times, users posted about how they spent a day or weekend with their colleagues. We applied this category when specific individuals were mentioned and tagged in an event post. What made these posts distinct was their emphasis on meeting a particular person or set of persons and explicitly mentioning them.
Observances
Our last category is Observance posts. These posts relate to charities and seasonal observances. Users sometimes appeal for donations or volunteers directly on LinkedIn. Some users specifically explained why they supported a specific philanthropic organization and requested their connections to donate their time or money to it. Another user shared that her daughter was selling Girl Scout Cookies and to support her by ordering cookies from a provided link. If the user was employed by the philanthropic organization, then we considered it a company post.
Not every post is a request for a time or monetary donation, however. Sometimes users post news updates about a social cause’s progress. Users might post about the philanthropic organization reaching a new milestone or successfully holding a past event. Overall, these posts provide information about a social cause without any call-to-action.
We also included seasonal observation posts such as holiday posts, awareness months, and remembrance days in this category. Posts saying seasonal solicitudes like “Wishing everyone a Happy New Year!” reflect this category. Posts commemorating remembrances like Martin Luther King Day were also in this category.
Which Topics Gets the Most Engagement?
We wanted to know whether certain categories garner more engagement than others. Since the five categories are not equal in frequency counts, we needed to a run a statistical test to make accurate comparisons. Below are the descriptive statistics for each type of engagement in Table 3.
Descriptive Statistics of Engagement by Category.
One thing to note is the high variability within the categories. To adequately compare differences, we tested assumptions to determine the best model. Shapiro-Wilk test results indicate that the number of reactions, comments, and reposts associated with each category does not follow a normal distribution (p < .05 for all categories and measures). Levene’s test for equality of variances also shows that the variances are not equal across the different categories (p < .05). Since neither of these assumptions held, we ran non-parametric tests to compare reactions, comments, and reposts across the categories using the Kruskal-Wallis H Test.
Which topics get the most reactions?
Our results showed a statistically significant difference in the mean number of reactions across categories, H(4) = .396, p < .001. Post-hoc analysis using Dunn’s method with a Bonferroni correction revealed significant differences between several comparisons in Table 4.
Pairwise Comparisons of Categories for Reactions.
Significance values have been adjusted by the Bonferroni correction for multiple tests.
Between Expertise and Observances (p = .027), the mean rank was higher in Observances (563.69) compared to Expertise (431.35). Otherwise, Interpersonal posts (594.92) showed a higher mean rank than Expertise (431.45, p = .000), Personal (490.95, p = .028), and Business (496.31, p = .021). Overall, Interpersonal posts showed higher amounts of reactions than most categories based on their mean ranks.
Which Topics Get the Most Comments?
Our results showed a statistically significant difference in the mean number of comments across categories, H(4) = 45.289, p < .001. Post-hoc analysis using Dunn’s method with a Bonferroni correction revealed significant differences between several comparisons in Table 5.
Pairwise Comparisons of Categories for Comments.
Significance values have been adjusted by the Bonferroni correction for multiple tests.
The mean rank for Personal posts (566.02) was higher than Business posts (458.32, p = .000) and Expertise posts (456.35, p = .000). Meanwhile, Interpersonal posts received more comments with a mean rank of 598.60 versus Expertise (456.35, p = .000), Business (458.32, p = .000), and Observances (461.94, p = .020).
Overall, Interpersonal posts once again showed a higher mean rank of comments than most categories. Personal posts also performed better than Business and Expertise posts.
Which Topics Get the Most Reposts?
Our results showed a statistically significant difference in the mean number of reposts across categories, H(4) = 91.464, p < .001. We conducted post-hoc pairwise comparisons using Dunn’s Bonferroni correction test to identify specific categories’ differences. We found significant differences in the mean rank of reposts between the following pairs displayed in Table 6.
Pairwise Comparisons of Categories for Reposts.
Significance values have been adjusted by the Bonferroni correction for multiple tests.
Business outperformed three other categories. The mean rank for Business posts (553.96) was higher than Personal posts (396.56, p = .000), Interpersonal (402.87, p = .000), and Expertise (553.96, p = .017). Observances also outperformed three other categories. The mean rank for Observances (649.64) outweighed Personal (396.56, p = .000), Interpersonal (402.87, p = .000), and Expertise (485.14, p = .000). Expertise had a higher mean rank of 485.14 over Personal’s 396.56 (p = .004). Otherwise, Interpersonal did not win any head-to-head comparisons in reposts.
Overall, Observances and Business posts dominate the other categories in reposts. Expertise outperformed Personal posts, but nothing else. Interpersonal posts did not beat other categories despite being dominant in reactions and comments.
Discussion
Our study aimed to achieve three outcomes: classify LinkedIn posts by topic, count the most frequent topics, and calculate the highest-performing topics in terms of their engagement metrics by reactions, comments, and reposts. The topics that generate the most engagement vary by each metric. Interpersonal and Observance posts won the most pairwise comparisons for reactions. Interpersonal and Personal posts won the most comments. Observance and Business posts won the most comparisons for reposts. Overall, we find that Interpersonal and Observance posts to be the most frequently winning topics compared to others across all metrics. Our findings lead to several points of discussion for LinkedIn as a platform and user engagement behaviors.
LinkedIn as a Platform
Our findings expand on previous studies of business accounts (Brewer & Imes, 2023; Mora Cortez et al., 2023). While we do not have a comparable study of post topics from business accounts, we now know that individuals post about topics that one would expect from a business account, such as job announcements and company news updates. We also learn that individual users also post personal topics, celebrate other individuals, offer expertise, and recognize observances. It is possible that business accounts post modified versions of these four other categories, but future studies are needed to further explore this.
We also learn that CEOs and individual users share this same tendency to post about their companies (Pérez-Serrano et al., 2020). However, a key difference is that individual users tend to post more personal branding topics like Expertise and Personal posts. CEOs, comparatively, post more about their company like financial results and corporate social responsibility. We offer two possible explanations for this difference. One could be that individual users may be more motivated to climb the corporate ladder via self-promotion and demonstrating expertise, whereas CEOs are already at the top and thus have less motivation to do that. Another could be that CEO LinkedIn accounts are monitored more closely by investors and one’s own communications team, so posts tend to be more business-oriented to avoid any social media controversies.
The fact that individual users frequently post about a company’s products, job openings, and news updates suggests that some users allocate their personal LinkedIn space to promote their company’s interests while other users do not. While organizational citizenship behavior is often studied face-to-face in the workplace (Organ, 2018), our study suggests it can extend to the digital realm via users’ LinkedIn profiles, creating a concept of digital organizational citizenship behavior where users offer their personal online spaces for their organization’s benefit.
Many users also post about other companies where they are not currently employed. We can only speculate why a user would post an update about another company. Some possible explanations might be pure fandom, a desire to get the company’s attention or to support another business out of charity. LinkedIn is not just a place to make a sale, it is also a way to serve as a referral and social proof for another business. LinkedIn is a platform for word-of-mouth marketing and self-advertising. Professional social media marketers can extend their reach by not relying solely on the company business page to inform users, but to have their regular employees deploy their personal LinkedIn pages as sites for promoting company interests.
By also showing that users frequently share content that aligns with their organization’s goals, such as job postings and company updates, our study also suggests that LinkedIn enables users to serve both their personal and company brands simultaneously through their topic choices. This dual motivation of personal branding and organizational representation illustrates a broader range of uses and gratifications that go beyond what Smith and Watkins’ (2023) study suggests. U&G theory, in its current form, might think too individualistically when it comes to LinkedIn and should consider company and professional goals. Future studies should consider the intertwined nature of both personal and organizational goals in digital professional networks.
Engagement
Our study also sheds light on LinkedIn user activity which has implications for engagement. First, to reach our sample of 1,001 posts, we had to visit 1,493 profiles. That means 34% of LinkedIn users have never posted. Granted, these users may comment, send messages, and interact in other ways on the platform that are not visible in a profile view. However, it still leads us to question why so many users do not use the posting feature. After all, the LinkedIn homepage feed is composed chiefly of posts, and it is how each user can communicate directly with their entire network. Moreover, the average post age was 499 days or 1.36 years. That means that the average user posts less than once a year. This trend contrasts with more frequent posting behaviors seen on other platforms, where users share content almost daily (Hruska & Maresova, 2020). Indeed, a Gallup Survey found that only 5% of LinkedIn users report that they frequently or occasionally post content on the platform compared to 35% of Facebook and 20% of Instagram users (Jones, 2023). When they do post, 43% of our collected sample was composed of reposts, which means that users are often repeating or responding to someone else’s post rather than composing from scratch. If we apply Kaye’s (2021) conceptual framework, LinkedIn users favor passive and reactive social media behaviors.
We can only speculate on the reasons for this trend without conducting surveys or interviews. One reason might be due to the lack of knowledge of what is appropriate to post on LinkedIn. Some mainstream articles provide professional post ideas discovered in our findings (Marrone, 2023), while others say LinkedIn posts are “getting personal and deep” (Abril, 2023). Meanwhile, The Guardian (Marks, 2024) published an article calling LinkedIn “a mess” and a “cesspool” that is “riddled with oversharing and lunatics.” There is also a Reddit (n.d.) forum with over 691,000 subscribers called r/LinkedInLunatics that shares “insufferable” LinkedIn posts for public scrutiny. Conflicting messages about what to post on LinkedIn may be a factor, especially when there is a risk of sounding like a “lunatic” if the post misfires. While many business communication and career development classes may have students write LinkedIn profiles, the other essential component for LinkedIn’s effectiveness is inspiring students to post and to understand its rhetorical situation. Such training can improve student outcomes on the platforms (Hazzam et al., 2024; López-Carril et al., 2022), and our findings can be a guide for students and educators on what to post.
Regarding engagement metrics, if a practitioner seeks to receive more reactions and comments, our study also suggests higher performing topics than Business posts. Our analysis shows that Interpersonal posts win more head-to-head comparisons in receiving reactions and comments than any other category. Observance posts were also undefeated in reactions and Personal posts performed well with comments only. The most frequent category, Business posts, performed poorly against them. While users may be drawn to posting about their companies and offering professional advice, these topics do not compete well against Interpersonal, Observance, and Personal posts in our analysis of reactions and comments. Our study was observational, so we can only speculate why Interpersonal posts win so many comparisons. A technical possibility is that interpersonal posts involve tagging other individuals, naturally increasing their reach when the tagged user receives a notification. A psychological possibility is that because a user’s LinkedIn feed shows so many Business and Expertise posts, perhaps an Interpersonal post speaks a deeper need for social connection that more users respond to per U&G theory.
However, the story changes with reposts. Interpersonal and Personal posts get reposted less than the other categories. Instead, Observance and Business posts perform better than most categories, each winning the most head-to-head comparisons. Unfortunately, the comparison between these two categories was not statistically significant, so we cannot break the tie. In any case, one can argue that reposting is the most impactful form of engagement because any repost extends the original post’s reach to the user’s network, which can then be reposted ad infinitum. Suppose a company tells its employees to share a post about a job opening. The employees post it on their personal LinkedIn pages, and each gets reposted twice by their networks. That company is now achieving its marketing goals of expanding its reach organically at an exponential pace. Why Observance and Business posts perform well with reposts is again subject to speculation. Reposts of Observances might be high because they are generally positive and reflect that a user cares about a social cause or holiday, fulfilling social integration needs. Users might repost Business topics so frequently because they include product promotions and job postings, which may be topics that users find the most logical to re-share for a quick repost.
Meanwhile, Expertise posts seemed to underperform overall against all other categories despite being the second most frequent in our sample. LinkedIn is a place for users to show that they are experts in their field and are aware of what is happening in their industry. Nevertheless, it only won one head-to-head comparison out of seven appearances, and that was with reposts. The reason for its performance level is subject to further study. One technical reason might be that 40% of Expertise posts are reposts sharing some media that direct the reader to an external site. These external links force the reader to leave the LinkedIn page, which may cause them to forget to engage with the post with a reaction, comment, or repost. We were not able to see a whether a post’s link was clicked on, known as a post’s click-through-rate (CTR), so it could be the case that Expertise posts are high performers in CTR, and that the lower amount of reactions and comments is a sign that users are engaging with the web link and immersing themselves into what is there (and not returning to their LinkedIn feeds). Perhaps it also has to do with the quality of the post and perceived information value of the advice. When users craft these posts effectively, they get reposted. When users craft them poorly, they suffer lower engagement than other categories. When one views the Reddit forum r/LinkedInLunatics, for example, many of the “lunatic” posts are ones of users trying to offer professional insights in tacky ways. Perhaps, poorly executed Expertise posts are judged more harshly and consequently receive less engagement. It can also be that information-seeking needs are harder to gratify on LinkedIn or are not truly what people use the platform for. More studies are needed to confirm.
Limitations and Future Research
Our exploration comes with sampling, coding, measurement, and statistical limitations that can be expanded upon in future research.
First, we based our findings on what was accessible to our networks, which are heavily composed of people in the Dallas-Fort Worth Metroplex and the Texas region. While this area is naturally diverse, there could be a regional bias in our dataset compared to a more evenly distributed one from other parts of the United States and worldwide. There have been no studies that have made regional comparisons of users on LinkedIn and their habits, so there is no way to know definitively of any specific differences. Thus, generalizability is uncertain with our results. A future study could investigate another region or use different search terms to make a comparison. Our use of only one post per user also subjects us to a data skew toward less active users versus ones who post frequently. However, our study’s design gave us a more representative sample of user activity.
Second, we single-coded our posts to run our statistics even though some were clearly multi-topical. For example, some posts started with professional advice and concluded with a product promotion. Other posts started with a career announcement and concluded with interpersonal gratitude. Before we consolidated our categories, we encountered 74 posts that could have been dual-coded. Instead, we went with our decision rules to single code each post. Those decision rules were based on what we perceive to be the primary intention of the poster and were listed in the Research Methodology section. Another study could have different decision rules that lead to a different frequency distribution and statistical results. Another study could also use dual codes to have a more granular understanding of how the topics intersperse themselves in a single post. That study could use our initial coding scheme for dual coding.
Third, our study was observational and measured engagement by only what was visible to us: the number of reactions, comments, and reposts. While these engagement markers are meaningful to users and social media strategists, our study does not investigate two other key performance markers: number of impressions and CTR. As we discussed, Expertise posts may get many views and have a high CTR on their shared weblinks and media content, even if they perform poorly in comments and reactions. LinkedIn provides a free post analytics page informing users of their post impressions but not CTR. Nevertheless, a future study could ask users to submit a post from one of the five categories and a screenshot of their analytics to further investigate the number of impressions and engagement.
Lastly, our study is all descriptive statistics and is not designed to be a predictive model of engagement. We did not control for any variables such as follower counts, job type, perceived credibility of the poster, demographic data, or the age of the post. Some studies suggest that these types of factors influence engagement counts (Petrovic et al., 2011). Nevertheless, a future study could develop a predictive model by controlling for these variables or by comparing users by grouping them accordingly. Additionally, an inferential study could also determine if any of the five categories are more likely to get engagement than others. Future studies could also achieve larger sample sizes, perhaps by using automated topic modeling instead of manual coding as demonstrated by Kobayashi et al. (2020).
Conclusions and Recommendations
Overall, our investigation finds that users promote their companies, offer professional insights, share personal achievements, praise other people, and observe holidays and social causes. Users most frequently post about their companies, mainly to promote their products and to share job openings. This is followed by offering their expertise via sharing tips and news articles about their field, followed by updates about their personal achievements. What gets the most engagement, however, depends on the user’s goals. Posts that praise other people get more reactions and comments overall, while posts about one’s own achievements get more comments only. Posts about social causes and business promotions get more reposts overall.
Theoretically, we show that users think beyond self-promotion and often serve their organization’s needs in their personal online space. U&G theory may thus have two layers of needs and gratifications to fulfill; a personal and professional level. Or perhaps, there is some personal need fulfilled by posting company victories, job advertisements, and updates in this new form of digital organizational citizenship behavior. Future surveys and interview studies can explore these phenomena considering our findings.
Educators can also use our findings to teach their students to post on LinkedIn. While creating a profile is an essential first step to building a LinkedIn presence, posting is the crucial second step. They can use our five categories and subcategories to help their students see the breadth of topics that they can post about as they complete their degrees and enter the workforce. Our study offers evidence for the normality of LinkedIn posts being more than self-promotion and career updates.
Practitioners can also learn from our findings that the winning strategy for engagement on LinkedIn may be less about promoting one’s achievements or attempting to show off expertise. Instead, it may be more about praising others, showing awareness of social causes and observances, and engaging in digital organizational citizenship behavior by promoting company interests. The best two performing of these categories are the least frequently appearing on LinkedIn and they are what seem to work.
Footnotes
Ethical Considerations
This study was reviewed by the University of Texas at Arlington Institutional Review Board (IRB) and was determined not to constitute human subjects research.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.