Original Article

Online Parasites: Concept, Characteristics, and Implications for Business Communication

Shaoyang Bu1, Joon Koh1,*
Author Information & Copyright
1School of Business Administration, Chonnam National University, Gwangju, Korea
*Corresponding author: Joon Koh, School of Business Administration, Chonnam National University, 77 Yongbong-Ro, Buk-Gu, Gwangju 61186, Korea, Tel: +82-62-530-1459, E-mail:kjoon@chonnam.ac.kr

Copyright © 2023 Korean Association for Business Communication. This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Received: Aug 23, 2022 ; Revised: Oct 27, 2022 ; Accepted: Nov 09, 2022

Published Online: Jan 31, 2023



This research, using the interview methods, attempts to identify a new type of network users which is called as “online parasites.” Since online parasites have a higher level of information retention and activity than ordinary passive users, companies that operate online communities should consider the needs and meaning of “online parasites” when activating inactive users.


This study conducted preliminary interviews with seven participants to observe how they use the internet, why they join the online community, and how they obtain information from the online community, regardless of whether they have the experience in posting messages in the online community.


This study explores the relationship between the active user, inactive user, lurker, and online parasite according to users’ interaction behaviors and the perceived contributions to the community. In addition, online parasites are defined as users who access and use the online community and produce interactive behaviors (such as likes and favorites) with the content but have no substantial content creation and contribution.


Compared to Lurker or passive receivers who read newspapers many years ago, most internet users now have a certain degree of enthusiasm like online parasites. Therefore, conceptualizing online parasites and studying their motivations and behaviors will greatly impact the sustainable development of the internet and virtual community.

Keywords: Online Parasite; Lurker; Interviews; Shadow Work; Active User


As the information society has rapidly progressed, the efficiency of searching for information has been emphasized, and efficiency has become a more meaningful measure. Message integration has played a crucial role in executing the delivery of more relevant and meaningful business messages in a cluttered communication environment (Jung, Kim, & Shin, 2022). However, the more information we encounter, the more stress we may experience. For example, Korhonen et al. (2018) found that when purchasing a product, the quality of product choice decreased as the quantity of information provided increased, with the latter making objective judgment difficult. Contact with large quantities of information can cause internet cognitive fatigue associated with motivations/impacts, behaviors, and empirical outcomes resulting from continuous mental work (Hong et al., 2015). Particularly on social media, instant messages often contain grammatical and spelling errors, internet slang, and abbreviations because they are poorly structured and limited to one or two words; all of these characteristics require additional cognitive processing (Chen, Lee, & Huang, 2018). Due to factors like cognitive fatigue, few netizens actively use the internet effectively.

Regarding online user participation, Nielsen (2006) has described low levels of involvement and information sharing as characteristics of the online environment adhering to the 90-9-1 rule. That is, 90% of users only read or observe (no contribution), 9% sometimes contribute, and the remaining 1% actively participate and provide most of the contributions. Most users already obtain information or consume media through the internet. In particular, younger millennials—who were previously under parental control—are becoming more self-driven, and they are used to directly searching for new information through the internet (Kim, 2019). Users who produce little or no content and perform other activities (e.g., reading quietly) are called “lurkers,” and their behavior is termed “lurking” (Gong, Lim, & Zhu, 2015; Ortiz, Chih, & Tsai, 2018). As lurking on the internet has become common, researchers have studied contributors and free-riders in collaborative governance (Choi & Robertson, 2019), information privacy and lurking behavior on social networking sites (Ortiz et al., 2018), role perspective analysis of social network latent intent (Liu, Min, Wu, & Liu, 2020), and lenses of transaction distance and interaction types of legitimate peripheral participants in online communities (Bozkurt, Koutropoulos, Singh, & Honeychurch, 2020). A study of social media established that the degree of lurking varied (Gong et al., 2015). Although the study did not grade the levels of lurking, the authors advocated its usefulness. Moreover, a survey of online review sites indicated that a group of passive users showed a high degree of participation (Munzel & Kunz, 2014). That is, not all passive users are characterized by inactivity on the internet combined with a negative attitude. Some passive users even engage in the online community, but do not contribute to it. They also actively obtain information from the network, but do not provide it. Thus, in this study, we define users who actively obtain desired information from the internet but largely do not contribute as “online parasites.”

Since passive users are the potential audience and customers, converting them into active participants has been regarded as an essential goal of online communities (Malinen, 2015). While it is particularly important to analyze and better understand passive users, few theories have been established by systematically approaching inactive users (Hwang & Lee, 2018). The purpose of this research was to investigate this new type of network user utilizing the interview method. Since they exhibit greater information retention and activity than ordinary passive users, companies operating online communities should consider the existence and needs of these “online parasites” when attempting to activate inactive users.

Literature Review

To research and classify internet users, the “active-passive” dichotomy appears to be the most common method, and most research has been focused on active, visible users. Active-passive quantitative measurements generally include the duration of membership, time spent on the internet, number of visits, number of clicks or views of the content, number of contributions, and density of social interaction with others (Malinen, 2015). For instance, YouTube users are mostly passive, with only a portion of them actively participating, and their rate of participation in active interaction with others is even lower. Interactive participants pursuing social relationships are relatively likely to view YouTube as an online community, while non-interactive and passive users utilize YouTube as a television-like channel (Shoham, Arora, & Al-Busaidi, 2013). In addition, participation in virtual communities includes passive viewing and active posting (Horng, 2016), or users may be classified as content contributors or content consumers (Engler & Alpar, 2018).

“Passive” typically refers to users whose access to technology is restricted (Pal, Pawar, Brewer, & Toyama, 2006). Regarding the concept of passive users, Wang, Gaskin, Rost, and Gentile (2018) interpreted active users as producers who contribute content such as updates and comments on other people’s posts, while they defined passive social networking service (SNS) users as directed or random consumers of social content. These users simply follow several chosen profiles and never generate any content that can be gathered or analyzed (Nechaev, Corcoglioniti, & Giuliano, 2017). The categorization of a user as active or passive appears to no longer be limited to the direct control of technology (Xu, Le, Deitermann, & Montague, 2014), but instead focuses on the user’s participation method and degree.

Notably, although researchers often develop new definitions, when defining lurkers, the non-creation of content and browsing behavior were mentioned at the same time. In addition, these definitions in the research do not consider the interactions between users and communities or between users and content (for example, clicking the “like” or “favorite” buttons). How do users perceive this interaction between users and content? Do they consider it a contribution to the community? This point is discussed in the Findings section of this study.

Finding suitable methods to study passive users poses a significant challenge because they usually remain in hiding and leave few traces, making it difficult to track their behavior (Soroka & Rafaeli, 2006). The advent of big data sets makes it more convenient than before to track the digital footprints of these passive users on networks. As such, lurkers and their passive activities can be better visualized by displaying website usage (Malinen, 2015). Nechaev et al. (2017) conducted a study on hiding digital footprints to protect the privacy of passive users who do not want to be noticed during activities on social media. Notably, lurking may not be the user behavior that social media companies expect. When a system lacks enough users who actively contribute content, the social media community may shrink (Gong et al., 2015). Practically, however, the presence of lurkers is meaningful. If every member of the community is involved in contribution, a huge quantity of repetitive information will be generated, requiring help filtering out what the users do not need (Koutropoulos, Honeychurch, & Singh, 2019).

Some lurkers are free-riders, but some lurk for other reasons, including pro-social and altruistic reasons (Edelmann, 2013). One reason is the demand for information. Here, the information-obtaining behavior can be considered “information-seeking behavior” or “information-searching behavior.” Moreover, Wilson (1981) suggested that “information need” was a secondary need that arose from the desire to satisfy primary needs. For example, the lurkers in the learning community pay more attention to their interaction with the content, that is, information acquisition needs (Bozkurt et al., 2020). Moreover, lurkers also propagate information or knowledge gained from the online community to others outside of it or use information or knowledge in their own or organizational activities (Takahashi, Fujimoto, & Yamasaki, 2003). In addition, employees who lurk do not openly seek help, but they do actively consume content (e.g., problems and solutions proposed by colleagues) to improve their business performance and meet expectations (Engler & Alpar, 2018). Thus, lurkers who do not contribute to the network, but rather actively obtain desired information from the internet for other purposes, exist.


Interview Procedure

We conducted preliminary interviews with seven participants to observe how they used the internet, why they joined online communities, and how they obtained information from the communities. Interviews were conducted from May 25, 2020 to July 7, 2020, and each interview took 25 minutes on average. We negotiated the location and time with each participant in advance and subsequently conducted a one-to-one interview at a cafe or quiet place near the participant’s school.

To facilitate the study analysis, the interview process was recorded with the participants’ consent, and the recording was taken using a smartphone. After the second interview, the contents of the interview were analyzed, and the third to seventh interviews were focused on information that required confirmation or elaboration. The transcription of the interview recording was taken by the researcher using software, followed by revision. The text of the interview after the transfer was 71 pages in total (A4 paper, 11-point, double line spacing).

Interview data were analyzed according to the grounded theory methodology (GTM), as presented by Strauss and Corbin (1990). Grounded theory is a systematic and flexible research method required to collect and analyze qualitative data to construct a data-based theory (Lee, 2015). Grounded theory is mainly used when the conceptual framework for a specific phenomenon is not clearly identified and a lack of understanding exists of the relationship between concepts, or when repeated research is not conducted on a specific problem (Park & Lee, 2017). Because this study was designed to delve into the understanding of online community usage behavior and business communication, as well as to explore a new user type, we judged it appropriate to use a grounded theory approach to analyze the collected qualitative data.

Composition of Interview Questions

The questions used in the interview were based on the research goals. They revolved around the use of personal networks and were structured as open questions to accurately capture the participants’ experiences. Table 1 lists the interview questions. During the interview, we made adjustments according to the situation, such as the sequence of questions and the way the interviewees answered.

Table 1. Interview questions
Do you use the internet often? How often?
Please explain how you feel when you use the internet.
Do you use any online communities frequently? Why?
What do you think about the online community you’re using?
Have you ever posted your thoughts or content online? Why?
Download Excel Table

The semi-structured questionnaire used in this study was based on the paper by Takahashi et al. (2003). In addition, to ensure the validity of the questionnaire content, participants were shown the transcribed interview text and asked whether it reflected their thoughts correctly and appropriately. This negated the subjectivity of the researcher, ensuring that the results would not contain distortions.

Selection of Participants

Current college students have grown along with the development of the internet, which they are accustomed to and can use proficiently. In a study on social media by Williams, Crittenden, Keo, and McCarty (2012), 80% of the research participants were college students who considered themselves to be spectators rather than active users of social media.

In a cross-border environment, it is possible to capture the diversity in experiences across various situations and cultures, such as by using a Chinese SNS versus a community or Korean SNS. For example, significant differences exist in internet usage (including average daily usage time, usage purpose, etc.) between Chinese students in Korea and Chinese students in China. Furthermore, the psychological maladjustment of Chinese students in South Korea and compulsive behavior related to internet use, as well as the degree of internet poisoning, are relatively prominent (Zhang, Kim, & Jang, 2015). Therefore, in this study, Chinese students over 20 years old who were studying in South Korea were selected as interview participants.

Characteristics of the Participants

In total, seven participants were selected for the interview. These included four men and three women, with a minimum age of 25 years and a maximum of 33 years, all of whom were graduate students majoring in electronic commerce (Table 2).

Table 2. Characteristics of the participants
Participant Age (year) Gender Education level Major
1 30 Female Graduate student Electronic commerce
2 27 Female Graduate student Electronic commerce
3 27 Male Graduate student Electronic commerce
4 33 Male Graduate student Electronic commerce
5 27 Female Graduate student Electronic commerce
6 25 Male Graduate student Electronic commerce
7 26 Male Graduate student Electronic commerce
Download Excel Table


We implemented in-depth interviews with seven interviewees. Based on the interviews, we attempted to identify the core themes related to each user’s online behaviors and user types using the GTM. The key findings of the interviews were the issues of (1) information needs, (2) interactive behaviors, (3) perceived community contributions, and (4) the online parasite as a new type of user.

Information Needs

Information-seeking behavior is the purposive seeking of information to satisfy some goal (Wilson, 2000). While seeking, the individual may interact with manual information systems (such as a newspaper or library) or with computer-based systems (such as the World Wide Web). Several interviewees stated that they used an SNS to meet their information and cognitive needs.

“When I don’t understand—for example, I may not understand what ‘free rider’ means, right?—I’ll go and see how someone else defines the term.” (Interviewee #1)

“If I am curious about a concept today, um... for example, I heard a classmate talk about something today, but I don’t know it, then I will look it up in Baidu to see what it is.” (Interviewee #5)

“I usually look at the trending searches on Weibo, those recommended to me. Then occasionally I will search for someone or something I am interested in.” (Interviewee #5)

“I hope that I can see some problems from a wider perspective, since there are professional writers on SNS. Then I look at current events, such as the current street-stall economy in China, and see how professional commentators evaluate this street-stall economy.” (Interviewee #7)

By acquiring information from the internet or SNS, users can receive help and solve problems in all aspects of work, study, and daily life. For personal shopping, evaluation information on products based on other people’s reviews can also impact purchase propensity. The participants also conveyed that the use of an SNS to obtain information is mainly due to the timeliness of this information acquisition method, the accuracy of information, and the comprehensiveness of information that can be obtained.

“In the comment area, the comments on a product help me a lot. For example, when I want to buy a product, I look at some favorable (or even unfavorable) reviews as well as the number of viewers and comments. The higher the number of comments, the more inclined I am to buy it.” (Interviewee #6)

“Since information on Weibo is not fake, it is a form of news or something. For instance, some information forwarded by the WeChat circle of my friends will not be verified. So, information from WeChat users can be forwarded directly, but those things that are trending on Weibo must be true.” (Interviewee #3)

Interactive Behaviors

At the level of interaction between users and the system, most interviewees expressed that they were unwilling to provide general contributions to the SNS community (in other words, to create content) due to the requirements of technical ability, time and energy, personality, and the SNS environment.

“For Douyin and Xiaohongshu, I have registered accounts, right? But I feel that shooting videos may require more technical expertise, so I have never posted anything on Douyin. ... I feel that you have to edit the video, which may cost you more energy and require technical knowledge.” (Interviewee #1)

“Because I am sensitive to my personal privacy, I don’t like to share my life with others. I think it is better to keep my personal life in my personal space. That’s why I don’t post on WeChat Moments, because I’m more inclined to write it out, to keep a diary or something like that.” (Interviewee #7)

Is clicking a “like” button a contribution behavior? Lee, Hansen, and Lee (2016) studied the “like” behavior on Facebook and stated that enjoyment was the main motivation for sample users to click “like.” “Enjoyment” means that the user likes the content, agrees with it, and relates to it, and the content is posted by a person who is important to them. In addition, a monetary incentive (such as receiving coupons or a bargain deal) also positively impacts “like” click behavior. We received the following information from the interviews:

“Sometimes I click ‘like.’ For example, for the football team I like, or the football player I love, um, I click ‘like’ sometimes. ... Zhiboba (the live-broadcasting platform) actually has two functions, ‘like’ and ‘dislike.’ When someone said something bad about my favorite player or team, I would leave a ‘dislike.’ ... Sometimes, for example, there is a lottery event on Weibo. I have shared the content of the event a few times, and I feel that, um, in this way I can participate in the lottery. If there is no reason to do so, I actually rarely publish the content.” (Interviewee #4)

From this perspective, the main reasons for clicking “like” include reflecting one’s own attitude toward others or the content, passing time, maintaining contact with others, and obtaining monetary rewards.

Perceived Community Contributions

Lurkers are generally defined as users who neither post nor contribute to the online community. Contributions include shared bookmarks and feeds, posts in forums, shared items in task lists, blog entries or comments, shared files, and new or revised Wiki pages (Muller, 2012). Never posting or commenting is interpreted as zero contribution (Wairimu & Andoh-Baidoo, 2018). In other words, users who neither publish content nor make the contributions detailed above can be called lurkers. However, Beike and Wirth-Beaumont (2005) define a lurker as an online community member who accesses and uses the online community but does not post messages. These users do not strengthen the community through reciprocal relationships in any form and have no direct social interaction with the community. Thus, the definition of lurkers is very vague from the perspective of user interactions with content.

Clearly, a user’s interactive behavior is primarily a reaction behavior stemming from the consideration of personal position. In other words, the individual will most likely not view it as a contribution. Perceived contribution refers to the user’s perception of the internet or the community, not the perspective of other members or the community.

“I feel like with the kind of posts that have been made, this should be regarded as a contribution. But if, um, just click ‘like’, would you say there was any contribution? Even if there is some, it feels too small.” (Interviewee #4)

However, from other perspectives, the user’s interaction with the community and content does contribute to the community. For example, ShareNcare is a Facebook-based social donation platform business that was established in 2015 to solve social problems through donations. On this website, the stories of people who need assistance are written and uploaded. If netizens click “like” or share the content after reading the story, the sponsoring company will donate instead of the netizens. Enterprises will also enjoy the publicity effect based on the spread of the story. In addition, the presence of many lurkers may increase the popularity of the community through their numbers, as they generate website traffic and increase clicks (Cullen & Morse, 2011). Alternatively, the lurkers leave evidence of having read the producer’s work, which can greatly inspire the producer (Edelmann, 2016).

“When users are actively using it, I think that is a contribution. For example, if an app is developed, if no one uses it, it will disappear, and it will not be improved. As soon as more users are present, it will actively be improved, and then the app will become more and more popular.” (Interviewee #2)

“In addition, for example, regarding some content, if ten people have shared it, whether it has likes or comments, no matter the form of interaction, it can be regarded as a contribution to the activity of the community.” (Interviewee #5)

The Online Parasite as a New Type of User

Based on users’ interactive behavior and perceived community contributions, we newly defined online parasites as users who access an online community and interact (as by liking and favoriting) with the content but add no substantial content creation or contribution. Although lurkers do not interact with community content or other members, they regard the SNS use itself as a way of contributing to the SNS company. However, parasites focus more on obtaining useful information from the SNS for their own purposes, and they do not consider the impact of their own usage on the company.

“I will try to do something simple, such as if the baby has a fever, right? If you search, it (‘Little Red Book’, a type of SNS in China) will tell you, for example, how to cool the baby down physically, right? So, I will try it.” (Interviewee #1)

“I don’t like comments very much, I think it’s for my own personal reasons, and I don’t like ‘likes’. I ‘like’ the content for a purpose, because then I can easily find the content I have watched in the ‘like’ list when I might want to watch the content again.” (Interviewee #2)

Here, we interpret “online parasites” as users who actively obtain desired information from, but do not contribute to, the internet. Terminologically, a parasite is an organism that lives in a host organism and receives its food from or at the expense of its host (Centers for Disease Control and Prevention, https://www.cdc.gov/parasites/about.html). This aligns with the meaning of online parasites described in this manuscript. That is, the dependence between people’s information needs and the internet is like the symbiotic relationship between parasites and their hosts; users benefit from the internet, and its information fills their nutritional needs. Their primary purpose is not, as with general passive users, to monitor other people’s lives such as by browsing and viewing people’s profiles or the contents of posts on an SNS (Verduyn et al., 2015). That is because processing information without contributing can be a high-performance, easy, socially supported, and resource-saving way to improve work efficiency. Online parasites are often strategic while participating in online activities, and thus spend considerable searching until they obtain the information they need. In other words, to satisfy primary needs (such as increasing awareness, improving professional skills, or solving problems), they will flexibly utilize the information obtained in an “active lurker as practitioner” fashion (Bozkurt et al., 2020).

Due to time and recognition limitations, increased role conflicts or role overloads can prevent users in the online community from responding effectively (Liu et al., 2020). However, this is not the case with online parasites. Online parasites more accurately see the online community as a channel to obtain information. They pay little attention to perfecting their personally identifiable information because it is not important relative to content. Moreover, they are also extremely talented in various environments and use multiple methods (such as search engines, blogs, SNS, and online communities) to achieve their goal of obtaining information for their own or organizational activities. They often use the “like” and “favorite” functions when they find content useful. It is convenient for them to view such content in the future and integrate it into their own information database or apply it to life and study. Since they are focused more on collecting information than on interacting with other users, they learn more in certain professional fields.

We suggest clarifying the relationships between the inactive user, lurker, and online parasite according to users’ interaction behaviors and perceived contributions to the community. Inactive users use the network passively; they need guidance and stimulation to cope with network changes. Although lurkers often use the internet, they rarely interact with content or other people because they do not want to leave any traces. However, they have a sense of value for their existence. The online parasite pays more attention to content and interacts with the interested parties. They are more self-centered and do not care about their contributions to other people and things, although they may accidentally take actions that contribute to the community.

We have provided a new definition for this category of users and clarified its relationship with similar user types, hoping to create an in-depth understanding of passive users and new insights for online community developers, managers, moderators, and software designers. Moreover, online parasites have abilities and resources to share, if we can find a suitable method to encourage them to produce and contribute content; this can make the online community more active and developed. As with existing methods, in conjunction with a reward mechanism, one could send them invitations and reminders to encourage the production of content to obtain access rights or spiritual or material rewards. Consequently, understanding the evolution and changes of users in the information environment has become particularly important to improve offerings.


Discussion and Implications

The development and evolution of the internet have provided a vast quantity of information resources for internet users to meet their needs. In this draft, we attempted to describe the so-called online parasites who primarily acquire information and knowledge by actively using the internet to achieve their goals. In this study, we explored only the characteristics of online parasites’ interactive behavior and perceived contribution. Although various types of interactive behaviors are performed by users of online communities, these behaviors can be collectively regarded as “digital shadow work” (Park, Lee, Koh, & Ryoo, 2020). While digital shadow work is generally thought to negatively impact consumers’ work behaviors, it is necessary to understand how it affects different types of users differently.

Digital shadow work is likely an important factor in various behaviors among different types of users. Digital shadow work is often understood as all unpaid work that users provide for businesses and organizations in the use of digital services, such as self-service operations. In the case of online communities, lurkers and inactive users minimize interactions with other members of the community and avoid digital shadow work as much as possible because they do not want to expose themselves. In contrast, active users and online parasites fulfill their own needs (e.g., self-expression or information needs) by performing digital shadow work. In addition, the reward mechanisms stipulated by the platform for different types of digital shadow work may also impact how users choose to participate in online communities.

Information has propelled most relationships for which people use the internet. Compared to lurkers or passive receivers who read newspapers many years ago, most internet users now possess a certain degree of enthusiasm, including online parasites. Therefore, conceptualizing online parasites and studying their motivations and behaviors will greatly impact the sustainable development of the internet and virtual community. This study has some theoretical and practical implications, as follows.

First, this draft confirms that information acquisition is a prominent motivation of online parasites, implying that marketers can satisfy the needs of these users by sharing various types of brand content. Although they seldom participate in business communication activities in the online community, they consistently monitor the progress of information, and they are very likely to become engaged in future business activities. Relative to other marketing activities or programs, providing brand content to online parasites is a cost-effective technique.

Second, when conducting business communication activities in online communities, the use of simple messages to promote products and content is usually emphasized. However, providing online parasites with more branded content and information is a relatively cost-effective way to deliver more relevant content and information than other marketing campaigns or programs, since detailed information is more attractive to these users.

Third, this study confirms that online parasites have a network addiction tendency; that is, they spend a substantial amount of time using the internet. Although network addiction is unhealthy for users’ well-being, it provides online marketers with more opportunities to interact with online parasites and promote brand information to them. This study suggests that online parasites are not valueless for firms. Understanding their psychological states and encouraging desired behaviors could help improve the firms’ marketing performance.

Finally, this study supports the following suggestions regarding how to convert lurkers or online parasites into active users. For lurkers, the basic proposed strategy is to reward these users to induce them to post. Compensation can be either intrinsic or extrinsic. Overall, this strategy is a method of quantitatively analyzing user propensity (based on connection frequency, residence time, number of views, interaction, etc.) and developing customized compensation policies. For passive users, the recommended strategy is to invite them to offline events (since even if the response rate is low, a small number will attend) and identify, educate, and utilize them as opinion leaders (Koh & Kim, 2003).

Study Limitations and Future Research Direction

Regarding the limitations of this study, first, the basic questions used in the interview were relatively simple, and more targeted questions should be designed. Limitations also existed in the sampling for the interview, which was a form of convenience sampling. The sampling included only Chinese students in Korea, producing a study sample that was very heterogeneous compared to other groups and very homogeneous within the group. Randomly choosing additional and diversified samples may enhance the validity and the generalizability of the findings. Furthermore, online behavior seems to strongly depend on the type of online communities with which the user interacts with as well as the context. That is, the same user may play different roles in different online communities. Thus, stronger evidence is required to support our conclusion.

Recommendations for future research are as follows. First, due to the limitations of a conceptual study like the present one, our argument still must be empirically validated. To this end, it may be a good method to develop measurement items and conduct quantitative research to provide empirical evidence for this classification. Deeper research is also necessary to explore the understanding of users’ online engagement behavior via focus group interviews. We cannot automatically categorize users into active and inactive users based on quantifiable information, such as the duration of online browsing or posting frequency. Thus, we must develop a sophisticated way of categorizing network users based on both quantity and quality indicators. To validate our idea of user type classification, additional detailed analysis is needed, along with in-depth discussion. In addition, it is desirable to consider more detailed behavioral comparisons between locals and foreigners (such as Korean and Chinese people in South Korea). Furthermore, new and advanced typology-related research on internet users is required.


In this article, we attempted to define a new type of network user termed the “online parasite,” who accesses and uses online communities and interacts with the content but engages in no substantial content creation or contribution. Using in-depth interviews of seven participants and the GTM, we found the core themes explaining the user’s online behavior and user type to be information needs, interactive behavior, and contribution to the community. Furthermore, by exploring the differences in various types of community users such as lurkers and inactive users, we provided several implications of the findings regarding the management of communities and firms’ community-based marketing strategies for converting lurkers or online parasites to active users. By proposing the definition of online parasites and identifying their characteristics, motivations, and behavior patterns, this article can not only provide new insights into community-based business communication but also contribute to the sustainable development of virtual communities.


This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2021S1A3A2A02089809).



Beike, D. R., & Wirth-Beaumont, E. T. (2005). Psychological closure as a memory phenomenon. Memory, 13(6), 574-593. .


Bozkurt, A., Koutropoulos, A., Singh, L., & Honeychurch, S. (2020). On lurking: Multiple perspectives on lurking within an educational community. The Internet and Higher Education, 44, 100709. .


Chen, C. H., Lee, W. P., & Huang, J. Y. (2018). Tracking and recognizing emotions in short text messages from online chatting services. Information Processing & Management, 54(6), 1325-1344. .


Choi, T., & Robertson, P. J. (2019). Contributors and free-riders in collaborative governance: A computational exploration of social motivation and its effects. Journal of Public Administration Research and Theory, 29(3), 394-413. .


Cullen, R., & Morse, S. (2011). Who’s contributing: Do personality traits influence the level and type of participation in online communities. Proceedings of the 44th Hawaii International Conference on System Sciences (pp. 1-11). Kauai, HI. .


Edelmann, N. (2013). Reviewing the definitions of “lurkers” and some implications for online research. Cyberpsychology, Behavior, and Social Networking, 16(9), 645-649. .


Edelmann, N. (2016). 13. What is lurking? A literature review of research on lurking. The Psychology of Social Networking, 1, 159-174. .


Engler, T. H., & Alpar, P. (2018). Contribution and consumption of content in enterprise social media. Information Systems Management, 35(1), 2-14. .


Gong, W., Lim, E. P., & Zhu, F. (2015). Characterizing silent users in social media communities. Proceedings of the 9th International AAAI Conference on Web and Social Media (vol. 9, no. 1, pp. 140-149). Oxford, UK. .


Hong, J. C., Hwang, M. Y., Chang, H. W., Tai, K. H., Kuo, Y. C., & Tsai, Y. H. (2015). Internet cognitive failure and fatigue relevant to learners’ self-regulation and learning progress in English vocabulary with a calibration scheme. Journal of Computer Assisted Learning, 31(5), 450-461. .


Horng, S. M. (2016). A study of active and passive user participation in virtual communities. Journal of Electronic Commerce Research, 17(4), 289-311..


Hwang, Y. Y., & Lee, K. Y. (2018). Factors associated with SNS users’ lurking intention. Journal of International Trade & Commerce, 14, 475-488. .


Jung, W., Kim, B., & Shin, S. (2022). The use of unified message system as a vehicle for effective mobile business communication: The case of morpheus message. Business Communication Research and Practice, 5(1), 14-19. .


Kim, B. (2019). ICT-based business communication with customers in the 4th industrial revolution era. Business Communication Research and Practice, 2(2), 55-61. .


Koh, J., & Kim, Y. G. (2003). Sense of virtual community: A conceptual framework and empirical validation. International Journal of Electronic Commerce, 8(2), 75-94. .


Korhonen, P. J., Malo, P., Pajala, T., Ravaja, N., Somervuori, O., & Wallenius, J. (2018). Context matters: The impact of product type, emotional attachment and information overload on choice quality. European Journal of Operational Research, 264(1), 270-279. .


Koutropoulos, A., Honeychurch, S., & Singh, L. (2019). Rethinking lurking. eLearn Magazine, 2019(5), 3. .


Lee, S. Y., Hansen, S. S., & Lee, J. K. (2016). What makes us click “like” on Facebook? Examining psychological, technological, and motivational factors on virtual endorsement. Computer Communications, 73(Part B), 332-341. .


Lee, W. K. (2015). The research issues and methodologies in non-use. The Journal of Information Systems, 24(3), 155-169. .


Liu, X., Min, Q., Wu, D., & Liu, Z. (2020). How does social network diversity affect users’ lurking intention toward social network services? A role perspective. Information & Management, 57(7), 103258. .


Malinen, S. (2015). Understanding user participation in online communities: A systematic literature review of empirical studies. Computers in Human Behavior, 46, 228-238. .


Muller, M. (2012). Lurking as personal trait or situational disposition: Lurking and contributing in enterprise social media. Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work (pp. 253-256). New York, NY. .


Munzel, A., & Kunz, W. H. (2014). Creators, multipliers, and lurkers: Who contributes and who benefits at online review sites. Journal of Service Management, 25(1), 49-74. .


Nechaev, Y., Corcoglioniti, F., & Giuliano, C. (2017, July). Concealing interests of passive users in social media. Retrieved from https://ceur-ws.org/Vol-1939/paper2.pdf.


Nielsen, J. (2006, October 8). The 90-9-1 rule for participation inequality in social media and online communities. Nielsen Norman Group. Retrieved from https://www.nngroup.com/articles/participation-inequality/.


Ortiz, J., Chih, W. H., & Tsai, F. S. (2018). Information privacy, consumer alienation, and lurking behavior in social networking sites. Computers in Human Behavior, 80, 143-157. .


Pal, J., Pawar, U. S., Brewer, E. A., & Toyama, K. (2006). The case for multi-user design for computer aided learning in developing regions. Proceedings of the 15th International Conference on World Wide Web (pp. 781-789). New York, NY. .


Park, S., & Lee, W. (2017). Using a grounded theory approach for understanding multichannel users’ crossover shopping behavior. Information Systems Review, 19(3), 179-199. .


Park, S., Lee, W., Koh, J., & Ryoo, S. (2020). Identifying shadow work mechanism in digital technology environments. Korean Management Review, 49(1), 31-50. .


Shoham, M. D., Arora, A. B., & Al-Busaidi, A. (2013). Writing on the wall: An online “community” of YouTube patrons as communication network or Cyber-Graffiti? Proceedings of the 46th Hawaii International Conference on System Sciences (pp. 3951-3960). Wailea, HI. .


Soroka, V., & Rafaeli, S. (2006). Invisible participants: How cultural capital relates to lurking behavior. Proceedings of the 15th International Conference on World Wide Web (pp. 163-172). New York, NY. .


Strauss, A., & Corbin, J. M. (1990). Basics of qualitative research: Grounded theory procedures and techniques. Thousand Oaks, CA: Sage..


Takahashi, M., Fujimoto, M., & Yamasaki, N. (2003). The active lurker: Influence of an in-house online community on its outside environment. ACM SIGGroup Bulletin, 24(1), 1-10. .


Verduyn, P., Lee, D. S., Park, J., Shablack, H., Orvell, A., Bayer, J., ... Kross, E. (2015). Passive Facebook usage undermines affective well-being: Experimental and longitudinal evidence. Journal of Experimental Psychology: General, 144(2), 480-488. .


Wairimu, J., & Andoh-Baidoo, F. K. (2018). Understanding lurking behaviors in open innovation communities: The role of social capital. Proceedings of the American Conference on Information Systems, Association for Information Systems. New Orleans, LA..


Wang, J. L., Gaskin, J., Rost, D. H., & Gentile, D. A. (2018). The reciprocal relationship between passive social networking site (SNS) usage and users’ subjective well-being. Social Science Computer Review, 36(5), 511-522. .


Williams, D. L., Crittenden, V. L., Keo, T., & McCarty, P. (2012). The use of social media: An exploratory study of usage among digital natives. Journal of Public Affairs, 12(2), 127-136. .


Wilson, T. D. (1981). On user studies and information needs. Journal of Documentation, 37(1), 3-15. .


Wilson, T. D. (2000). Human information behavior. Informing Science: The International Journal of an Emerging Transdiscipline, 3(2), 49-56. .


Xu, J., Le, K., Deitermann, A., & Montague, E. (2014). How different types of users develop trust in technology: A qualitative analysis of the antecedents of active and passive user trust in a shared technology. Applied Ergonomics, 45(6), 1495-1503. .


Zhang, L., Kim, S. Y., & Jang, M. S. (2015). Internet usage and psychological maladaptation comparison of Chinese students studying in Korean university and Chinese university. Rehabilitation Therapy Education, 7(2), 167-180..