published quarterly by the university of borås, sweden

vol. 25 no. 3, September, 2020

Leading factors that explain engagement in closed Facebook groups

Judit Bar-Ilan, Tali Gazit, and Yair Amichai-Hamburger

Introduction. Facebook groups are a popular way to communicate and exchange information. This is reinforced when membership of the particular group forms an important part of that member’s identity.
Method. The authors joined closed Facebook groups and studied the factors that enhance engagement from within. This study used a mixed method: 1) the level of engagement in closed Facebook groups was coded for 274 group members over a two-month period: the number of posts, comments and ‘likes’ were counted for each participant; 2) an online survey was answered by these participants, containing demographic questions, a group importance questionnaire, an offline activity measure and a Big5 personality questionnaire.
Analysis. The data were collected into Excel, with a sheet for each participant, and then transferred to SPSS for statistical analyses.
Results. There is a positive relationships between engagement, group importance, and offline activity. Women and stable, older participants tended to engage more in group discussions. A partial, positive relationship between extroversion and engagement was found.
Conclusion. The findings give groups’ managers and members tools to enhance higher engagement in Facebook groups, which may sustain the online community as a dynamic social group, where all members have equal rights to engage.


Online discussion groups allow people with similar interests to express opinions or give feedback on someone else's post, discuss common problems and issues and offer information and support on a variety of topics (Bronstein et al., 2016). The literature distinguishes between 'posters' and 'lurkers' (e.g., Amichai-Hamburger et al., 2016; Gazit et al., 2018). Posters are active members of online communities who are generally regarded as more constructive and are considered essential for sustaining the online community as a dynamic social group (Cullen and Morse, 2011). Lurkers, on the other hand, read social media data but do not directly contribute and prefer passive attention over active participation (Gazit et al., 2018; Rafaeli et al., 2004). Too many lurkers in an online group are liable to result in problems that face online communities such as a low posting rate and lack of valuable content (Sun et al., 2014).

The level of engagement, as an aspect of online behaviour, is also important from the users' point of view. Earlier research has found that online engagement enhances social well-being (van Uden-Kraan et al, 2008), has a positive influence on social self-esteem, and reduces levels of stress and depression (Herrero et al., 2004). Regarding lurkers, researchers found that passive use of social networks sites may undermine users’ subjective well-being (Wang et al., 2018). In a study that investigated an online smoking cessation discussion group, higher levels of participation predicted social identification and smoking cessation self-efficacy (Phua, 2014). People’s attention toward user-generated comments on Facebook affect recipients’ public opinion perceptions which, in turn, influence subjects’ opinions and their willingness to engage in social media discussions (Neubaum and Krämer, 2017). Thus, there is a great importance for a variety of voices sharing their ideas from a democratic point of view (Perez et al., 2018). Hence, users - especially lurkers - should be encouraged to engage more actively in online discussions.

Various studies were carried out relating different factors with online engagement, most of them were using surveys (Bronstein et al., 2016; de Lenne et al., 2020). The current research delved into the engagement in closed Facebook groups. Closed groups on Facebook can be found by conducting a simple search or by being invited by an existing member. The members in the closed groups can be seen, but, unlike public groups, unless you are a member – you cannot see the content of the group. In order to get accepted as a member, usually the group's Admin should authorise membership (Miron and Ravid, 2015). This study used closed Facebook groups because they enabled tracking lurkers as well as active participants by manually coding their activity in the groups. This study explored how the following variables: demographic variables (age and sex), personality traits (extroversion/introversion, openness to experience, neuroticism, agreeableness and consciousness), group importance and level of offline activity can explain engagement in Facebook groups. This way, we got a wider and clearer picture regarding the different aspects that enhance active participation in virtual groups where all members have equal rights to engage and sustain the online community as a dynamic social group.

The aim of the study was to understand what factors can predict engagement in closed Facebook groups, since it has been shown previously that active participation enhances well-being (Herrero et al., 2004; Wang et al., 2018) and lurking leads to lower quality discussions (Sun et al., 2014).

More specifically, the objectives of this study were to explore to what extent do the following variables explain engagement in Facebook groups: sex, personality traits (extroversion/introversion, openness to experience, neuroticism, agreeableness and consciousness), level of offline activity of the same topic and group importance.

Literature review

The literature specifies a variety of factors that come into play when people determine their engagement (Amichai-Hamburger et al., 2016; Gazit et al., 2018; Sun et al., 2014). A survey that distinguished between posters and lurkers in professional virtual communities revealed different motives for posters and lurkers. Posters displayed a positive correlation between their attitude towards sharing knowledge and enjoyment in helping others. For lurkers, a positive correlation between attitude towards sharing knowledge and perceived ease of use was found (Hung et al., 2015). Bronstein et al. (2016) found, also through a survey, that motivations to participate were mediators between variables like openness to experience or offline activity and participation level in various virtual platforms.

The current research delved into closed Facebook groups, figuring the factors behind engagement through the combination between a survey (demographic factors, personality factors, offline activity and group importance) and actual coding (level of engagement). Facebook groups are defined as 'spaces where you can share things with the people who care about them most' (Facebook newsroom, 2012). Indeed, being in an online group strengthens the members' mutual identity and enhances their self-esteem. It allows them to express themselves in a way that has no parallel any other environment (Amichai-Hamburger and Hayat 2017; Wong et al., 2017).

Sex and psychological traits

Nonnecke’s (2000) study claimed that there are a proportion of individuals who are predisposed to lurk and those who are predisposed to post. Concerning sex, women tend to use Facebook more than men (Hargittai, 2015). They update more their profile photos, change their statuses more often (Wang et al., 2012), write more public posts and use social network sites to preserve social relationships more than men (Muscanell and Guadagno, 2012). Women also report higher collective self-esteem in a group than men (Barker, 2009).

Concerning psychological traits, Cullen and Morse (2011) suggested that different personality traits are related to different motives to become active members of the online community. Previous studies have found a relationship between personality traits (McCrae and John, 1992) and participation behaviour (Gazit et al., 2019; Amichai-Hamburger and Vinitzky, 2010). Openness to experience and extroversion are particularly conspicuous: it was found that individuals who display a higher level of openness to experience in their personality traits engage more in online groups and extroverted people engage in social media sites (Gazit and Aharony, 2018; Gazit et al., 2019) and in Facebook chat rooms (Hong et al., 2014) more than introverts. However, other studies suggested that introverted individuals would be expected to display higher levels of online engagement than in face-to-face personal interactions. This is particularly true when they interact in an anonymous environment in an attempt to meet their social and intimacy needs (Amichai-Hamburger et al., 2016). Even though most Facebook profiles present full and true identification of the users (Facebook newsroom, 2018), in Facebook groups members do not necessarily know each other, which might make them feel that they are in a more anonymous and protected environment. Hence, the uniqueness of the Facebook groups environment re-raises the question of the relationship between personality traits and engagement.

Offline activity and group's importance

Research has shown that users of social media sites tend to replicate the behaviour that they exhibit in face-to-face interactions (Amichai-Hamburger and Hayat, 2013). Indeed, a previous study found that the more active people are offline, the more active they will be in online groups (Bronstein et al., 2016). The link between offline and online behaviour might be the importance of the subject (Gazit, 2017). The importance of a group is defined as being associated with respondents' feelings about the significance they attributed to the group in their daily routine (Aharony and Gazit, 2016). Amichai-Hamburger et al. (2016) suggest that when individuals feel that there is no match between them and the group, they are unlikely to remain active within it. Rafaeli et al. (2004) found that to be more active, one should feel very comfortable with the group. Another study found that if participants receive a response to their first post, they are likely to participate again (Joyce and Kraut, 2006).

Other factors that are shown to be related to the group’s importance that enhance higher engagement include the level of group intimacy (Phua, 2014; Rau et al., 2008), the quality of information given in discussions (Lee et al., 2006), the speed and frequency of response, and the users' perception of the importance of the subjects under discussion (Cheng and Liu, 2012). Gazit et al. (2018) interviewed active participants and lurkers through focus groups and found that once the subject of the discussion was relevant to them, both lurkers and active participants were encouraged to take an active part in the discussion. Aharony and Gazit (2016) investigated WhatsApp family groups and found that openness to experience and social support were in positive correlation with the group's importance. A previous study that examined political online activity prior to the United States presidential elections in 2008 revealed a positive relationship between users' perception of Facebook as important and online political activity (Vitak et al., 2011). Finally, a recent study investigating Facebook support groups for women with fertility problems revealed that the group importance is the strongest prediction of the level of engagement in the group (Gazit and Amichai-Hamburger, 2020).

The current study

One of the growing types of online social discussions groups are groups on Facebook, the most popular social media site (Perrin and Anderson, 2019). On Facebook users receive a selection of daily updates of different activities and publications in their news feed, including groups they are members in. This study focuses on closed Facebook groups because they guarantee discussions of very specific subjects and their members have shared interests. Examination of closed Facebook groups also enables the posts to be coded and older posts in the group can be accessed. In addition, in most of the groups (as opposed to Facebook pages), everyone is allowed equally to express their opinions by posting, commenting and liking (Miron and Ravid, 2015). Finally, Facebook groups permit the members' level of engagement to be identified. That includes lurkers, who are usually very difficult to study, since even though they do not participate at all, they are registered as group members and can be coded and approached. These unique characteristics of closed Facebook groups make the current study important and innovative, so it allows us to take a closer look at users’ personality and behaviour in a real, closed, virtual group.

The following research hypotheses were developed based on the studies discussed above and the nature of the personality characteristics being examined:



Choosing the Facebook groups. We first searched for active, closed groups that covered different topics and were small enough (up to 200 members) for us to be able to follow manually each group member's engagement. We asked people around us to tell us about groups they are familiar with and found around thirty of them. Most of them contained thousands of members and some were not active enough. Hence, out of the groups that were examined, only five were both small and active. The five groups that were chosen provided the variety of subjects required for the study and fulfilled the strict requirements: All groups were closed, active groups, with two or three posts a day and with fewer than 200 members. Permission for the group to participate in the study was then obtained from the group administrators. Two refused to cooperate, leaving us with three groups. The following groups were included in the study: volunteers who raise guide dog puppies (199 members); geeks (167 members); and Israeli Wikipedia editors (138 members). After receiving the administrators' permission, the data from these groups were analysed at two levels: members' personal engagement level and the data from questionnaires of those who agreed to participate and filled it out. The study was approved by the Faculty’s Institutional Review Board Committee.

The individual participants. A total of 274 Israeli participants agreed to complete the questionnaire and to be coded in the Facebook group: 127 from the group of volunteers who raise guide dog puppies (64%), 90 from the Geek group (54%) and 57 from the Israeli Wikipedia Editors group (41%). Of the 274 participants, 157 were women (57.3%) and 117 were men (42.7%). Table 1 presents the distribution of the participants according to the groups and sex.

Table 1: The distribution of the participants according to groups and sex
Volunteers who raise guide dog puppiesWomen8528.617.51
Men2928.17 6.48
Wikipedia editorsWomen1136.6011.48
Men11731.83 10.25
Total27429.92 8.80

Tools and measures

We used mixed methods in this research: an online questionnaire to collect all the personal data and systematic coding to follow each participant's engagement level. Members have signed an informed consent form, telling them that only past posts will be coded, and that their identity will not be revealed.

The questionnaire

Group members completed an online questionnaire by following a link that was attached to a post in each group. The questionnaire comprised several sections - each was considered to serve as an independent variable:

Coding each member's engagement level in the group.

One hundred and fifty posts that were published in each of the three groups before the request to complete a questionnaire were coded over a period of approximately two months. The coding was done by two undergraduate, third year, psychology students who received payment for their work. The total number of posts, comments, and likes created by each of the 274 participants were recorded using 274 separate Excel spread sheets. Each participant's posts, comments, and 'likes' were recorded in separate columns on the spread sheet, and a point was given for each post, comment, and "like". The total number of points was then calculated for each participant and each feature (posts, comments, 'likes') to determine their engagement level.

Engagement level. The engagement level of each group member comprised the dependent variable in this research. The following criteria were based on Gazit's (2017) research, in which the coded engagement level was significantly and strongly correlated with what the participants reported about their own perception of engagement level on a five-point Likert scale. In order to determine the level of engagement of each group member, the coders had a list of all the group members who completed the questionnaires. Members of the group who completed the questionnaire, but were not coded in any category (post, comment or 'like') were coded as lurkers. In order to rank the different engagement levels, an algorithm was created that took into account the number of likes, comments and posts each member posted, creating a new variable: Engagement level. The engagement level was determined according to the following criteria:

Figure 1 shows the distribution of the engagement levels according to the groups.

Figure 1: Engagement according to the groups

Figure 1: Engagement according to the groups


Sex differences

A one-way ANOVA test was conducted to examine whether there were significant differences between sexes in the research variables. The results are presented in table 2.

Table 2: ANOVA test: Differences in the research variables between sexes: means, standard deviations, F-test values and eta squared values (N=274).
VariableWomen (N=157) Men (N=117)F-test Eta squared
Group importance3.780.903.320.8618.14***0.06
Offline activity3.031.472.681.384.15*0.02
Extroversion 3.380.783.130.746.94**0.03
Openness to experience3.800.653.840.610.150.00
*p<0.05 **p<0.01 ***p<0.001

Table 2 shows that there are significant differences between men and women in all the variables except for agreeableness and openness to experience. The other variables, including engagement, were found to be significantly higher among women than among men.

Personality traits, offline activity and the group's importance

Pearson product-moment correlation coefficients were computed to examine the relationship between engagement and the independent variables group importance, offline activity and the five personality traits: extroversion, neuroticism, agreeableness, consciousness, and openness to experience. These correlations are presented in Table 3.

Table 3: Pearson product-moment correlation coefficients between engagement and all study variables (N=274)
Variable12 3 4 5 678
1 Group importance0.42** 0.040.14*0.040.02-0.040.53**
2 Offline activity 0.15*0.120.07-0.010.22**0.38**
3 Extroversion -0.24**0.100.30**0.27**0.08
4 Neuroticism -0.31**-0.40**0.14*-0.01
5 Agreeableness 0.29**0.100.09
6 Consciousness  -0.100.05
7 Openness to experience 0.04
8 Engagement 
Standard deviation0.901.440.770.780.530.640.641.42
*p<0.05 **p<0.001

Table 3 shows that there are no significant correlations between the personality traits and engagement (p > 0.05). However, significant positive correlations were found between the dependent variable engagement and the independent variables: group importance (r = 0.53, p < 0.001) and offline activity (r = 0.38, p < 0.001). In addition, there is a significant positive correlation between group importance and offline activity (r = 0.42, p < 0.001).

Since no correlations were found between engagement and the five personality traits, the variables were examined separately for each group. Significant but low positive correlations were found between engagement and extroversion (r = 0.18, p < 0.05) and between engagement and consciousness (r = 0.21, p < 0.05) only within the Guide Dog Puppy Raisers' group.

Predicting the engagement level

Considering the correlation and differences that were found in this study, a hierarchical regression analysis was conducted to predict engagement. The hierarchical regression was conducted to find mediators and interactions (Baron and Kenny, 1986). The predictors were entered as five steps: 1 - demographic variables (sex and age); 2 - Facebook groups: to allow the differences between the groups to be shown in the regression model two dummy variables were created: 'Dogs' with the two values: belonging to the Guide Dog Puppy Raisers' group or not; 'Wiki' with the two values: belonging to the Wikipedia Editors group or not; 3 - the BIG5 personality traits: extroversion, openness to experience, neuroticism, agreeableness, and consciousness; 4 - group importance; 5 - offline activity; and 6 - interactions between all variables. The introduction of the first five steps in the regression model was forced, while that of the interactions was entered according to their contribution to the explained variance. It is only worthwhile to include interactions in which the significance level is lower than 0.05 in the regression. Consequently, only the age x neuroticism interaction was included in the regression. Table 4 presents the standardised and unstandardised coefficients of the hierarchical regression of the engagement level in Facebook groups. In the analysis we found that 35.7% of the variance in the engagement level could be explained by the research variables.

Table 4: Hierarchical regression coefficients of the explained variance of engagement (N = 274)
0.01 0.04
3. Extroversion
4.Group importance 0.860.56**0.27**0.33**
5.Offline activity0.150.16**0.02**0.35**
6.Age x Neuroticism-0.16-0.11*0.01*0.36*
*p<0.05 **p<0.001

The first step introduced the demographic variables, of which the sex variable contributed significantly by adding 3% to the explained variance of the engagement. The beta coefficient of the sex variable was significant, indicating that engagement among women was significantly higher than among men. The second step introduced the groups' dummy variables, which did not contribute significantly to the explained variance of engagement. The third step, which introduced the five personality traits also did not contribute significantly to the explained variance of engagement. The fourth step introduced the variable of group importance, which contributed significantly by adding 27% to the explained variance of engagement. Hence, the higher the group importance, the higher the engagement level. The fifth step introduced the offline activity variable, which contributed significantly by adding 2% to the explained variance of engagement. Hence, the higher the level of offline activity, the higher the engagement level. In the sixth step interaction between age x neuroticism was entered, which added 1% to the explained variance of engagement. The interaction of age x neuroticism is presented in Figure 2.

Figure 2: The interaction between neuroticism and age for engagement

Figure 2: The interaction between neuroticism and age for engagement

According to Figure 2 there is a positive relationship between age and engagement among stable participants (low neuroticism) (β = 0.17, p < 0.05), while no relationship was found between age and engagement among highly neurotic participants (β = -0.06, p > 0.05). Thus, engagement increases with age, but only among stable participants.


The current research examined the dynamics behind the unique platform of closed Facebook groups in a mixed method that combined questionnaires and coding. The questionnaires revealed the participants' demographic details, their personality characteristics, their offline activity level and how important the group was for them. The coding revealed their actual engagement. This combination enabled a better understanding of the personal factors that can enhance active participation in virtual groups where all members have equal rights to participate and sustain the online community as a dynamic social group.

The present study examined to what extent the variables sex, age, the BIG5 personality traits, offline activity and group importance explain engagement in closed Facebook groups.

The purpose of this study was to identify the predictors of engagement in Facebook groups. This was done using a manual coding assessment of Facebook groups. Results showed that only about 27% of the members of the groups were lurkers. In actuality, only half of the members were either lurkers or had low levels of engagement, while the other half were found to be at least moderately or more than moderately active. This is an encouraging finding since our results show much higher activity levels than previous studies, where a majority was found to be passive members (e.g., Han, et al., 2014; Nonnecke, 2000; Rafaeli, et al., 2004). It seems that when Facebook groups are created "naturally" and without coercion or necessity and members join voluntarily, members have interest in being more engaged since the topic of the group is particularly relevant to them.

Four of the research hypotheses were confirmed, one was partially confirmed, and one was refuted. H1 focused on the differences between men and women and was confirmed. We found that women have a higher level of engagement, offline activity and perception of group importance than men. This finding contradicts a previous study in which a higher level of verbal and emotional intimacy was found among men, who consequently engaged more than women (Rau et al., 2008). However, our findings are supported by more current studies that found that women tend to update their profile photos, write statuses (Wang et al., 2012), write public posts and use social network sites to preserve social relationships more than men (Muscanell and Guadagno, 2012). Women also report higher collective self-esteem in a group than men (Barker, 2009). The later finding can explain the higher rating of group importance that women gave to their group in this study as well as their higher online and offline engagement.

H2 focused on the relationship between the personality trait extroversion and engagement. This hypothesis was only partially confirmed, as it was found to be true in one group only. This finding is supported by a previous study that examined these personality traits and the level of participation in social network sites. The study found that extrovert people find their "true selves" in more traditional ways of communication outside the Internet than introverted people (Amichai-Hamburger et al., 2002). The absence of a significant correlation between extroversion and engagement can also be understood by the fact that on Facebook groups, introverts may feel safe enough to express themselves as they do not know most of the other members, and thus they may feel there is a likelihood that they will receive a positive response (Amichai-Hamburger et al., 2016). There may also be differences in the degree of spontaneity of the response. Introverts may take more time to structure their response but will participate in group discussions. It is noteworthy that this lack of correlation is supported by the findings of Ross et al. (2009) and that Tang et al. (2016) did not find any relationships between extroversion or openness to experience and addiction to Facebook.

However, we found a positive correlation between extroversion and engagement in the Guide Dog Puppy Raisers' group. Unlike the other two groups, this group was originally created offline. This can be explained by the 'rich get richer' perspective (Amichai-Hamburger et al., 2008), which argues that when an offline group transfers to online, the same patterns of dominance among participants will also be transposed. This will result in the extrovert members, who were dominant offline, continuing to hold this position online. Consequently, when the group moved from offline to online, only the 'rich' (the extroverts) 'got richer' namely engaged more, while the introverts continued to engage less. In contrast, to the best of our knowledge, members of the other two groups were only acquainted with one another virtually, which afforded those members who were not extroverts, more chance to express themselves in the online group.

H3 focused on the relationship between the personality trait openness to experience and engagement. This hypothesis was refuted. Although significant relationships were found between extroversion and openness to experience and offline activity, no significant correlation for online activity was found between openness to experience and engagement.

Although previous studies found relationships between the personality traits of extroversion and openness to experience and engagement in social media sites (e.g., Aharony, 2013; Bronstein, et al., 2016; Gazit et al., 2018), these studies used self-evaluation measurements to examine the participants' subjective feelings about their engagement. This study determined engagement using coded participation, a method that, to the best of our knowledge, was not used previously in Facebook groups. In addition, these previous studies based their findings upon the participant's personal sites/pages, while this study examined the participants' behaviour in a closed group. Once a person joins a group, the group's dynamics may become more meaningful than his/her personal traits that play a secondary role or even lose their importance within the array of considerations for activity as the group's identity becomes more meaningful and powerful than the personal identity (Taylor et al., 1990).

H4 concerned the relationship between offline activity and engagement, and H5 on the relationship between group importance and engagement. Both hypotheses were confirmed. Findings showed that the higher the level of offline activity and the higher the perception of group importance, the higher the engagement will be. The significant relationship between these three variables is supported by a previous study that examined political online activity before the United States presidential elections in 2008. The findings of that study also showed a positive relationship between Facebook importance, offline activity, and online political activity (Vitak et al., 2011). Although the current study did not examine political activity, one can assume that being a member in a Facebook group implies an interest in the group that corresponds to offline and online engagement. The relationship between offline and online engagement is also supported by a previous study that found a positive correlation between the two through an online questionnaire (Bronstein et al., 2016).

An additional finding was revealed in the regression analysis. In addition to sex, group importance and offline activity that predict the dependent variable engagement, the interaction age x neuroticism was also found to be a predictor of engagement. Even though we did not find a significant relationship between age and engagement, other studies found a positive relationship in which the older the people were, the more they used WhatsApp groups (Gazit and Aharony, 2018) and Facebook (Aharony, 2013). Aharony's study also revealed a negative relationship between age and neuroticism and a positive relationship between neuroticism and Facebook use. In the current study an interaction was found between age and neuroticism that sheds more light on the complexity of these relationships. Stable participants (with low neuroticism) who were older tended to engage more in Facebook groups, while no such relationship was found among highly neurotic people. Hence, Facebook groups enable stable, older people to express themselves more than younger people. There was no significant difference according to age among more neurotic people, a finding that is supported by studies that found that neurotic people tend to share more in social media sites during any period in their life (e.g., Amichai-Hamburger and Vinitzky, 2010).

Conclusions and study limitations

Today, Facebook groups are one of the most popular ways to communicate and exchange information, especially in groups of shared interests. This research investigated the unique platform of Facebook groups by showing the personal factors that explain engagement in the group. The mixed methods used allowed us to reveal both the individuals' personality traits and perceptions and to observe their online behaviour by coding their engagement.

The aim of the study was to understand what factors can predict engagement in closed Facebook groups, since it has been shown previously that active participation enhances well-being (Herrero et al., 2004; Wang et al., 2018) and lurking leads to lower quality discussions (Sun et al., 2014). The correlations found between the coded engagement, the group importance and the offline activity are innovative and may be used as a base for understanding the nature of behaviour in Facebook groups. Hence, for example, groups' administrators may generate offline meetings between the group members and thereby promote a higher level of group importance and a higher level of engagement within the online activity. Future research can examine administrators' strategies that help their group members to become more engaged. According to the results, we can also understand better the level of engagement of the groups' members upon their profiles. For example, if an individual is a woman, who cares about her Facebook group, is active offline, young and psychologically stable, there is a good chance that her Facebook group will hear her voice in the discussions.

This study contributes to knowledge about the predictors of engagement and lurking in Facebook groups, but has several limitations. First, not all the group members completed the questionnaire, hence the activities of some of the members were not coded. Consequently, we were unable to receive the exact percentage of lurkers and active participants in each Facebook group. Secondly, engagement was coded over a specific period of time. The group may have meant more or less to certain members at a particular point in time which could result in higher or lower engagement, resulting in different group activity. This notion is supported by the significant relationship that was found between group importance and engagement. Finally, we studied three specific groups, which may not be representative enough for all Facebook groups. The reason for doing so was the manual coding that was complicated and time consuming. Future research should find a way to code individuals' participation level automatically in Facebook groups, so that a greater variety of groups can be coded.

About the authors

The late Prof. Judit Bar-Ilan (1958-2019). Judit Bar-Ilan was professor at the Department of Information Science of Bar-Ilan University in Israel. She received her PhD in computer science from the Hebrew University of Jerusalem and started her research in information science in the mid-1990s at the School of Library, Archive and Information Studies of the Hebrew University of Jerusalem. She moved to the Department of Information Science at Bar-Ilan University in 2002. Her areas of interest included: informetrics, information retrieval, Internet research, information behaviour, and usability. Prof. Bar-Ilan received ASIS&T's Research in Information Science Award in 2018. Sadly, she passed away last July. Her detailed CV and list of publications can be found at http://is.biu.ac.il/en/judit.
This paper is published in the honour of her memory.
Tali Gazit is a senior faculty member in the Department of Information Science, Bar-Ilan University (Israel). She holds a PhD in Internet Psychology from the Department of Information Science, Bar-Ilan University. Her research interests are Psychological and environmental factors of engagement and lurking in online discussions, social media groups and communities, well-being and Internet, virtual leaders and information literacy. Dr. Gazit can be contacted at: tal.gazit@biu.ac.il +972-52-8432534. She is the corresponding author.
Prof. Yair Amichai-Hamburger received his Ph.D. from Oxford University. He is the director of the Research Center for Internet Psychology (CIP), based at the Sammy Ofer School of Communications at the Interdisciplinary Center (IDC) in Herzliya, Israel. He has worked for many years as an industrial consultant, advising many leading organizations. He has written widely on the impact of the Internet on well-being. His first book, The Social Net: Human behaviour in Cyberspace, was published by Oxford University Press 2005 and his second book, Technology and Psychological Well-being, by Cambridge University. His third book The Social Net: Understanding Our Online behaviour was published by Oxford University Press 2013. Prof. Amichai-Hamburger can be contacted at: +972-99527649, yairah@idc.ac.il


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How to cite this paper

Bar-Ilan, J., Gazit, T., & Amichai-Hamburger, Y. (2020). Leading factors that explain engagement in closed Facebook groups. Information Research, 25(3), paper 866. http://InformationR.net/ir/25-3/paper866.html (Archived by the Internet Archive at https://bit.ly/3gC6UH7)

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