The cyberspace environment presents a variety of activities and human behaviours. Examples include new academic and stimulating environments, open learning (Al-Rahmi et al. 2022), and social and human capital (Benson et al. 2019). During the COVID-19 pandemic, academic institutions across the globe underwent a complete transition to online activities, significantly augmenting their dependence on cyberspace. This transition led to the exploration of new academic environments and social interactions, and open learning opportunities. Consequently, the pandemic amplified the importance of the cyberspace environment for facilitating academic activities.

Yet, research has also shown the negative consequences of the extensive use of Information, Communication, and Technology (ICT). Deviant behaviour is likely to occur online, in workplaces and academic contexts (Fissel et al. 2020), such as cyberloafing, when employees access the internet at work for personal use while pretending to do legitimate work (Tandon et al. 2021), cyberbullying (CB) (Abaido 2020) and cyberstalking (CS) (Stevens et al. 2021).

CB is defined as a ‘willful and repeated harm inflicted through the use of computers, cell phones, and electronic devices’ (Hinduja and Patchin 2014a, 1). CB includes sending, posting, or sharing negative, harmful, false, or malicious content about someone else, causing embarrassment or humiliation (Olweus 1993; Hinduja and Patchin 2014b). The cyberbully intends to intimidate and disparage the victim and can also steal confidential material or write threatening comments through electronic communications (Marcum and Higgins 2019). CB can occur in many forms: denigration (posting untrue information), flaming (hostile and insulting interaction), harassment (insults or taunts with repetitive messaging or posts), and outing (revealing personal information without permission) (Hinduja and Patchin 2014a; Marcum and Higgins 2019).

CS is defined as the repeated use of electronic communications to harass or frighten someone persistently, for example, by sending threatening emails or finding out information about victims (Kraft and Wang 2010). CS behaviours relate to harassment and intimidation and may include spying, monitoring, or controlling the victim’s behaviour (e.g., hidden webcams, SpyWare, and GPS devices). Cyberstalkers may also pursue and contact their victims anonymously through fake online profiles (Shorey et al. 2015; Smoker and March 2017). Their behaviour may include monitoring, false accusations, defamation, slander, and libel (Ronsefeld 2004).

Online victimisation, through CB and CS, affects students (Kowalski and Limber 2013), especially more vulnerable groups (Kowalski et al. 2016), and staff (e.g., lecturers and admins) in Higher Education (HE) context (i.e., universities) (Larrañaga et al. 2018; Heiman and Olenik-Shemesh 2019; see also Stevens et al. 2021 for a systematic review).

Yet, there are no precise statistics on the prevalence of CB and CS among undergraduate students and academic staff. According to the Working to Halt Online Abuse website, in 2013, approximately 38% of CS victims were aged between 18 and 29, reflecting the age of most HE students. Besides, rates of CB prevalence were high in HE student populations even before the COVID-19 pandemic, ranging between 6 and 35% in the studied samples (Bottino et al. 2015; Kamali 2015). These figures raise concerns for CB/CS in academic communities, especially after the COVID-19 pandemic, which possibly increased risk factors (Heiman and Olenik-Shemesh 2022; Oksanen et al. 2022). Associated behaviours such as increased use of social media may also have impacted increased victimisation (Kaur et al. 2021).

A recent systematic review (Bussu et al. forthcoming) highlights a gap in the literature relating to CS and CB behaviour and their impact on staff and students as victims on university campuses (Oksasen et al., 2021), especially during and post pandemic. CB (Abaido 2020) and CS (Stevens et al. 2021) have been investigated independently in the workplace and academic context rather than jointly (e.g., Al-Rahmi et al. 2022; Heiman and Olenik-Shemesh 2022).

The present study provides a novel investigation of cyberbullying and cyberstalking victimisation, exploring students and staff experiences during the COVID-19 pandemic when online activities, including virtual classes, and remote work increased. This unprecedented online sharing may have exposed users to extra risk and thus represents an opportunity to examine the challenges faced by these two groups regarding CB and CS. The aim is to offer insights into common experiences, vulnerability, perceived organizational responses and support mechanisms in a university community.

Literature review

Melander’s research highlighted the transformative impact of technology on student relationships and revealed new modalities for perpetrating psychological aggression characterized by “quick and easy violence” (2010, 266). Shaikh et al. (2021) highlight that, due to the COVID-19 pandemic, academic staff and students have increased their use of mobile devices, ICT, and social media networks (e.g., Twitter, Facebook) in their everyday lives. These platforms facilitate communication among colleagues and students, with mobile apps like WhatsApp, Discord, Snapchat, and emails being used to exchange academic and personal information (e.g., Zakar et al. 2021). While this shift brought positive outcomes, such as the adoption of innovative teaching methods and the adherence to social distancing protocols, it also raised concerns about the increased risk of deviant cyber behaviours within HE settings. The pandemic emergency further enhanced the global shift towards remote work, significantly transforming the work environment for many individuals compared to pre-COVID-19.

Kowalski et al. (2020) found that more than 45% of their respondents had been victims of CB at least once. However, other studies, such as Zhong et al. (2021), reported a lower prevalence rate of CB. Additionally, Saeed et al. (2021) conducted a cross-sectional survey involving 272 students to investigate CS in higher education during the pandemic. The findings indicate that most respondents demonstrated explicit awareness of social media regulations and CS behaviors.

CB and CS are also associated with detrimental consequences for victims, characterized by distressing and intrusive behaviors facilitated through computers, cell phones, and electronic devices that disrupt relationship formation, online communication, and social identity (Marcum and Higgins 2019). Moreover, these adverse cyber behaviours can lead to financial burdens. Victims may incur tangible costs, including medical expenses and loss of income, and intangible costs such as poor academic performance, social isolation, psychological distress, and the onset of psychological disorders (Fissel et al. 2020; Kaur et al. 2021).

Other studies highlighted negative impacts on the well-being and academic performance of students. For instance, Alsawalqa (2021) revealed a detrimental impact on students’ self-esteem. Similarly, Yang (2021) found that the coping strategies employed by college students during COVID-19 lockdowns were affected. Additionally, Al-Rahmi et al. (2022) identified the negative moderating role of CB and CS in terms of learning success. These authors also reported that collaborative learning suffered from the adverse effects of CB due to its impact on student relationships. Previous research also uncovered the presence of cultural variations in the coping strategies employed to address cybervictimisation, thus emphasising the significance of cross-cultural investigations (Wright et al. 2018; Bussu et al. forthcoming). Notably, most of the studies on CB and CS focus on the United States university system, which is notably different from other Western Countries (e.g., European countries, Canada, Australia, and New Zealand), and non-Western Countries (e.g., Africa, Asia, India). Souza et al. (2018) further asserted that the association between experiencing victimisation and engaging in cyberbullying as an aggressor is primarily influenced by psychosocial campus climate and cultural factors.

Several recent studies identified a correlation between CB and psychological distress, which can be attributed to the increased reliance on remote access and online teaching during the pandemic lockdowns (Barlett et al. 2021; Shoib et al. 2022). Furthermore, Lee et al. (2022) highlighted that systematic reviews consistently reported a significant association between CB victimization and various psychological disorders, including social and behavioral problems (Shaikh et al. 2021).

Regarding academic staff, a survey conducted by Oksanen et al. (2022) revealed that 30% of the participants reported experiencing online harassment within the previous six months. The victims were predominantly senior staff or individuals belonging to minority groups in social sciences and humanities. Additionally, several studies specifically emphasised the adverse impact of the pandemic on both mental and physical health (Das et al. 2020; Holmes et al. 2020). At the same time, research on both CB and CS indicated a significant association between cybervictimisation and severe mental health problems, particularly during the pandemic (Martínez-Monteagudo et al. 2020).

Hence, empirical evidence suggests that the pandemic posed a new victimisation risk for academic students and staff and also raised concerns about the prevalence of CB via social media (Karmakar and Das 2020; Daigle et al. 2021). Barlett et al. (2021) found a correlation between COVID-19 experiences and CB perpetration, with direct experiences of victimisation increasing the likelihood of becoming a CB perpetrator. These studies highlight the need for implementing mitigation strategies to support vulnerable groups during future traumatic events.

Existing literature primarily relies on quantitative methods to study CB and CS affecting students (Karmakar and Das 2020; Martínez-Monteagudo et al. 2020), staff (Oksanen 2022) as two separate groups (e.g., Alsawalqa 2021; Hossain 2021). However, investigating both groups together is crucial since they belong to the same community and face similar challenges. From a methodological perspective, there is a notable lack of qualitative research on the perception of CS and CB’s impact in higher education especially during and after the pandemic, which prevents the planning of adequate institutional support for victims (Meter et al. 2021; Harrison et al. 2022). Indeed, qualitative research offers valuable insights into complex interrelationships and behaviours, providing richer and more in-depth information.

There is a consensus among researchers that more education and informed resources are needed to address CB (Meter et al. 2021) and CS (Karmakar and Das 2020) to prevent and manage aggressive online behaviours. Meter’s (2021) study revealed that participants lacked training and pertinent information on CB during their adolescence and were unfamiliar with procedures and academic protocols. Notably, there is limited research discussing policies on CB and CS for students and staff in higher education, particularly in the post-pandemic context (Marcum and Higgins 2019; Mace et al. 2016; Wozencroft et al. 2015).

Research rationale and research questions

University and college student samples have been extensively studied. However, most studies (see, e.g. Kamali 2015; Kaur et al. 2021) focus on cyberbullying or cyberstalking. There are several reasons for exploring CB and CS jointly in an academic context, involving students and staff.

(1) CB and CS research in HE lacks consistent definitions. CB and CS tend to be confused regarding their definition by victims and often overlap in Higher Education (Bauman and Baldasare 2015; Huang and Chou 2010; Ronsefeld 2004; Steven et al. 2021). In this respect, CB is mainly used for adolescents, while CS and cyber-harassment are often used to describe adult behaviours (Kamali 2015).

CB (Abaido 2020) and CS (Stevens 2021) have been investigated in the workplace and academic context independently but not together (Fissel and Reyns 2020).

CB and CS lack consistent definitions, and both behaviours are under-researched in HE environments (Oksanen et al. 2022; Kamali 2015), especially regarding staff. This definition inconsistency has led to a scarcity of policies, especially during and post-pandemic. Furthermore, as noted by Oksanen et al. (2020, 2021), CB overlaps with harassment, but it has typically been investigated in the context of school and, only more recently, in the workplace (Kowalski et al. 2018; Oksanen et al. 2020; Wan Rosli et al. 2021; Zych et al. 2015). HE environments include both contexts but remain under-researched (Oksanen et al. 2021).

(2) Studying students and staff jointly Students and staff are vulnerable because social network sites (e.g., Facebook, Snapchat, Twitter, Google, YouTube, Wikipedia and other Mobile Devices Application (MDAs)) that are part of their everyday social lives and education. Students and staff share information (e.g., about academic issues) via chat (i.e., WhatsApp, Instagram, Snapchat, Discord) with other students or colleagues also outside formal lectures. These activities increase the risks of CS and CB victimisation.

A limited number of studies discuss policies on CS and CB for students and staff in HE (Arafa and Senosy 2017; Mace et al. 2016; Marcum and Higgins 2019; Wozencroft et al. 2015). In comparison with the school context (Kowalski et al. 2018; Oksanen et al. 2020; Polanin et al. 2022; Zych et al. 2015), there is a gap in our understanding of risk factors, impacts and, consequently, best practices and prevention strategies at the university level for supporting students and staff.

As a novel research thread, it is appropriate to collect survey data from various ages and population groups (e.g., staff), and to triangulate richer information through different methodologies (Marcum and Higgins 2019). Notably, the academic staff (academic and admin groups) is still under-researched (Stevens et al. 2021). In a pre-pandemic qualitative study on cyberstalking, cyberharassment and cyberbullying against students and staff, Short et al. (2016) showed that online communication is ambiguous and there is a need for the promotion of online norms to which young people and staff can adhere. Furthermore, participants were generally unaware of academic policy for preventing these adverse behaviours (see also Oksanen et al. 2021).

A recent study published by Oksanen et al. (2021), based on nationally representative data from university staff in Finland, revealed that 30% of the participants experienced online harassment during the prior six months; participants also showed higher levels of post-traumatic stress disorder (PTSD) symptoms. Furthermore, very few victims reported the assaults to supervisors or the police.

It would be helpful to assess whether CB and CS consequences are similar for students and staff and, on this basis, plan preventive and supportive programs for each category.

(3) Need to explore cybervictimisation in HE during the COVID-19 pandemic. As previously mentioned, the pandemic and subsequent lockdowns have prompted concerns regarding their potential contribution to social stigma and the increased prevalence of CB victimization through social media. A recent study by Barlett et al. (2021, cited in Shoib et al. 2022) showed that the stresses of being diagnosed with COVID-19 or knowing infected people were often associated with cybervictimisation and cyberbullying.

There are no precise statistics on the prevalence of CB and CS among undergraduate students before and during the pandemic. However, one recent study on adolescents in schools in South Korea examined the prevalence of CB and the risk factors before and during the COVID-19 pandemic (2019 and 2020). They found that the phenomenon decreased (Shin and Choi 2021), possibly due to increased awareness of CB issues by teachers, families and children during this time.

So far, the literature has not provided a qualitative paper on victims of CB and CS in HE (i.e. students and staff) during the pandemic. Such research can provide insight into the phenomenon and outline preventive measures and policies for on campus support for victims.

(4) Lack of clear policies for students and staff. The final reason for exploring CB and CS in HE is that neither has received adequate international attention, UK included (see e.g. Myers and Cowie 2019), leading to a lack of clear policies for students and staff (e.g., Kamali 2015; Alotaibi 2019). Studies have highlighted gaps in the literature and the importance of implementing research on CB and CS within an HE context to develop new protocols and best practices (e.g. Ahlgrim and Terrance 2021; Kaur et al. 2021; Kraft and Wang 2010; Marcum et al. 2016; Marcum and  Higgins 2019; Pereira et al. 2016; Reyns 2019; Reyns et al. 2018; Walker et al. 2011).

This paper explores the impact of CS and CB on the everyday lives of students and staff and will explore potential strategies to counteract cybervictimisation. In this respect, investigating this phenomenon in HE will provide information on how best to prioritise student and academic well-being, and how to promote a safer digital world post-pandemic.

Although increased research has focused on CB and CS over the past decade, there has been limited qualitative work to obtain a clear understanding of both cyber behaviours among students and staff on university campuses (Alexy et al. 2005). There is also limited empirical evidence to evaluate the impact on staff and students as victims. According to Naidoo (2020), institutions need to implement further cybercrime research into CS and CB, collect and compare evidence and design effective countermeasures to ensure a safer digital environment, especially in times of distress. ‘A safer digital world can help us cope with many of the other pressing challenges during the pandemic and new challenges that can be expected in the post-pandemic future.’ (Naidoo 2020, 27).

This paper explores victims’ perceptions of cyberbullying and cyberstalking in a HE context, in the United Kingdom (UK), during the COVID-19 pandemic. An online semi-structured questionnaire was administered to students and academic staff to elicit richer information on cyberbullying and/or cyberstalking experiences. A qualitative analysis explores the consequences of these adverse events regarding their impact on lives and well-being.

Based on gaps in the literature, the following research questions are addressed in this paper:

  • RQ1. What were victim perceptions about their experiences of CB and CS during COVID-19? This research question explores victim experiences and perceptions concerning online adverse events during the pandemic lockdowns.

  • RQ2. Did victims experience any impact or changes in their lives because of the CB and CB as adverse events during COVID-19? This research question explores the vulnerability of victims and examines whether they faced any negative consequences or alterations in their lives due to their experiences with CB and CS during the pandemic. In this way, the study offers an exploratory insight into the broader ramifications of online cybervictimisation on victim well-being and daily routine.

  • RQ3. Are there any differences between students and staff? This third research question assesses whether there were common factors in the experiences of students and staff regarding online cybervictimisation, emotions and resilience mechanisms.

These research questions will be investigated using qualitative data to provide an explorative understanding of the phenomenon under analysis. Qualitative analysis helps understand participant perceptions, vulnerability, impact, resilience, and perceived support mechanisms within a university community.


Sample and procedures

A convenience sampling technique targeted students and academic staff at a university in the North-West of England. This sampling method is commonly used in qualitative research for demographically and geographically local samples, thus restricting generalisation to that local level (Robinson 2014; Etikan et al. 2016). It also retrieves sensitive information from a target population likely to be involved as victims of CB and CS.

An online survey decreases error margins because the information is collected from the best-fit respondents anonymously and voluntarily. A further advantage relates to the sample’s ability to communicate adverse experiences with a higher level of awareness in a more articulated and reflective way (Kerlinger 2014). As selection criteria, the survey was available to all university adult students and staff (academic and admin). As an initial filter, participants had to self-identify as CB and/or CS victims during the pandemic. No sample filters were applied regarding ethnicity, gender, age and role. All these criteria were explained in detail in the invitation letter and the participation information sheet.

The online survey was available for eight months. We collected 34 complete semi-structured sections of the questionnaire; on average, they took approximately 30 min. The online and anonymous survey was self-administered and consisted of self-reported measures and open questions intended to gather data on CS and CB events. The research team promoted the study across all the faculties by email. Ethical clearance was obtained from the Ethics Committee at a UK university.

The survey provided an information sheet about the research project, and participants were required to complete a consent form, which was submitted electronically. The participant information sheet included instructions on withdrawing from the study if necessary and provided the institutional contact details for the Principal Investigator and the Associate Dean of the Faculty. Each completed semi-structured questionnaire was linked to a unique identification number (ID) associated with participants, enabling them to withdraw their consent anonymously, if necessary. The online survey was promoted and disseminated through various internal mailing groups at the university to gain maximum exposure, in line with previous research (Faucher et al. 2014; Marraccini et al. 2015). The authors stressed that the project was run independently of the university, and participant anonymity will be maintained at all the project stages.

Study design

Recent studies (e.g., Harrison et al. 2022) have shown that collecting qualitative data, especially victim perspectives, can help address a methodological gap in the research related to CB and CS in HE contexts. In addition, the qualitative approach revealed richer information about victims' emotions, opinions, behaviours/changes, and personal consequences during the pandemic. Based on the literature, the semi-structured section of an online questionnaire explored participants’ CB and CS experiences (see Sheridan et al. 2001; Spitzbergen and Hoobler 2002; Walker et al. 2011). The survey consisted of four main sections, as follows:

Section 1)  Demographics. This section recorded age, gender, ethnic background, university role (staff or student), faculty, and living arrangements.

Section 2) Relationship between the victim and the cyberstalker/cyberbully. This section focused on the cyberstalker/cyberbully. Any prior relationship between victims and cyberstalker/cyberbully; the duration and frequency of the cyber behaviour; nature and course of the cyberstalking; the perceived impact; specific behaviour of the CS/CB offender; the reaction of the victim; the response of the authorities; and finally, sources of support available for victims (Sheridan et al. 2001; Walker et al. 2011).

Section 3) CB and CS behaviour. We also adopted an Electronic Use Pursuit Behavioral Index (EUPBI) (Strawhun et al. 2013). This self-reported questionnaire asks respondents to specify if they have been a victim in a series of CS and CB events.

Section 4) Open questions, the participants were invited to answer open questions on their CB and CS experiences, the impact on their life, offence reporting, and suggestions on prevention strategies and service facilities. This information enabled us to explore practical actions adopted by the victims to protect and support themselves and any specific recommendations they wished to provide to academic institutions for helping victims of CB and CS behaviour. This paper will present and discuss the data that emerged from Sections 1, 2, and 4 of the questionnaire.

Data analysis

A thematic analysis explores participant opinions regarding their experiences of victimisation and elicits suggestions for supporting victims more effectively (Clarke & Braun 2013). An interpretative approach reconstructs the ‘implicit theories’ of the respondents (Ross 1989; Ashton and Bussu 2020). According to Ross (1989, 1), “People possess implicit theories regarding the inherent consistency of their attributes, as well as a set of principles concerning the conditions that are likely to promote personal change or stability (…); people use their implicit theories of self to construct their personal histories”.

A rigorous methodological process was adopted for coding and analysis while avoiding the loss of valuable information. All the interviews were transcribed verbatim with written permission from the participants. Data gathered from the respondents’ narratives were analysed using ATLAS.ti 7.5 Two researchers carried out the coding and analysis, but there was continuous feedback from the whole research team (internal coding) throughout the coding process.

The software ATLAS.ti assists in the accomplishment of the thematic analysis and methodologies/frameworks (e.g. grounded theory, content analysis, and thematic analysis) (see, e.g. Archer et al. 2017; Janis 2022). The ATLAS.ti coding process is not hierarchical but rather inductive. The software provides the “ability to express relationships between codes, concepts, and themes in a range of different ways, and often these cannot be represented in a hierarchical list” (Silver and Lewins 2014, 210). A qualitative text analysis elicits themes that resemble and summarise the meaning of participants’ responses (Thematic coding, also defined as thematic analysis). The frequency of codes and themes was also detected. ATLAS.ti network summarises the interpretation process, which was iterative and progressive. In this respect, the researchers reflected on various conceptual issues and unveiled new central aspects. Every code in each network includes two numbers: the number on the left represents the frequency of a given code within the transcriptions; the number on the right refers to the number of direct associations (Bussu 2016).

The data were analysed according to the criteria set by Patton (2002). The quality criteria (i.e., credibility; transferability; dependability; authenticity; confirmability) proposed by Seale (1999) were applied (Table 1 Quality Criteria Guidelines). A triangulation technique was implemented to validate the data through cross-verification from two sources (qualitative and quantitative data collection methods). Indeed, methodological triangulation can more accurately identify multifaceted aspects by approaching the same phenomenon from different perspectives and using other methods and techniques (Greene 2006). However, this paper presents the main findings from the qualitative data that were collected.

Table 1 Quality criteria guidelines


Socio-demographic data, victims and cyber offender relationship

The sample consisted of 25 females (73.5%) and 9 males. The sample age median was 38.5 years old. Respondents were balanced regarding the age segments: 18–25 years, n = 10; 26–35 years, n = 6; ≥ years 36, n = 16. There were 22 staff members (65% of the sample: 20 academics and 2 administrators) and 12 students (equivalent to a quota of 35%).

Concerning their ethnicity, 94.1% declared white (British, Irish and/or other white backgrounds), and 5.9% Asian (Asian/Asian British Indian and Pakistani).

One noteworthy finding is that 65% of the respondents in the sample comprised staff members. This outstanding observation is particularly significant given the limited research on staff, as existing studies predominantly concentrate on cyber safety within the school and youth population. Most participants (47.1%) declared that they were victims of CB, 29.4% of CS, and 23.5% were both CB and CS victims (see Table 2).

Table 2 Descriptive statistics

Beyond these numerical percentages, the qualitative insights provided by respondents significantly enhance our understanding of victimization (see also Table 3). Staff stated that when they were victims of CB, usually the cyberbully was either work-related (student or colleague) or a stranger; a similar result was found for victims of both offences. CS occurred more frequently because of adverse behaviour of ex-partners or strangers. The perpetrators of student CB were typically either a university contact or stranger and, less frequently, an ex-partner or friend. Students were also victims of CS by ex-partners or friends. Interestingly, two of the student cyberstalkers were strangers. One student was a victim of CB and CS, and the ex-partner committed both offences. The ‘perpetrator work related’ (students and colleagues) and ‘stranger’ were more common for the staff than the students. In comparison (RQ3), the perpetrators of student victimisation were primarily an ex-partner, a student/colleague, or a friend rather than a stranger.

Table 3 Victims and cyber offender relationship

These findings accord with a previous study that focused on academic staff during the pandemic (Oksanen et al. 2022). The perpetrator was a member of the respondent’s work community (17.8%), and very often, the victims knew the perpetrators (43.0%) compared to 33.1% of the sample who reported that the perpetrator was a stranger. In previous research by Cassidy et al. (2016), staff were victims of CB either by students and/or colleagues. In both studies, as in the present research, the victims were usually females. Regarding the staff and according to our research and previous studies, it seems relevant to explore stranger perpetrators who offend female staff members. The males in our sample were all academic staff members, while the students were all females.

Main qualitative findings and discussion

After analysing the data, we decided not to provide specific sections for CB and CS outcomes because the patterns of victimisation were very similar, especially regarding the central theme that emerged from the qualitative analysis. We consider it more beneficial to discuss the victim's self-perceptions of the impact of both cyberbehaviours and to explore their reactions to the phenomenon. Where relevant, we have compared the experiences of students and staff (RQ3) to offer a holistic approach to the problem in a HE context.

From the thematic analysis, 101 macro-codes, six families, and 26 memos emerged. Every code in each network (Fig. 1, 2) includes two numbers: the first number represents the frequency of a given code within primary documents (qualitative responses) provided in the hermeneutic unit. At the same time, the latter refers to the number of direct associations with other codes. ATLAS.ti networks and quotations (Q) are commented on to examine and represent the main findings. Specifically, the following thematic areas were identified by the analysis, as perceived by the respondents.

Fig. 1
figure 1

Victim perception of Cyberbullying and Cyberstalking during COVID-19

Fig. 2
figure 2

Impact of Cyberbullying and Cyberstalking on the victims

Victim perception of cyberbullying and cyberstalking during COVID-19 (RQ1-RQ3)

CB and/or CS victims were asked to share lifestyle adaptations before and during the pandemic. Where changes occurred, they were asked to explain why. Most of the sample (17 staff members and 12 students) believed both cyber behaviours increased during the pandemic. This result confirms previous research by Barlett et al. (2021) and Kaur et al. (2021), where their participants perceived that CB and CS increased during COVID-19. Nevertheless, there is no particular difference concerning CB/CS. While both phenomena are equally crucial in HE, CB appears more common in the academic context than CS (Table 4). The victims also explored potential reasons for motivating their perception, as discussed below (RQ1- RQ3).

Table 4 Self-perception of cyberstalking and cyberbullying during pandemic
Staff: social media networks and the academic online workload during the lockdown

Academic staff and students believed the diffusion of social networks, mobile device applications (MDA), and innovation technology during the pandemic increased (Extract 1) (Fig. 1, Q29:11, Q33:12). Overall, ICT impacted CB and CS (e.g., Facebook, Twitter and WhatsApp) (Extract 2). Cybercrimes in workplaces are increasing due to students and staff using more social networks (Fig. 1, Q30:11; Q29:11) and due to people feeling more frustrated and anxious because of COVID-19 (Fig. 1, Q12:11; Q28:12), as also addressed in the literature (e.g., Zakar et al. 2021).

Ex 1  “As a result of people’s reliance upon social networks more than ever. People are turning their attention away from physical interactions and directing them more towards digital interactions” (Staff, male)

Ex 2 “I believe that Cyberbullying at work is increasing because we use more social networks/ innovative technologies, and it is also directly associated with the workload.” (Staff, female)

Staff claimed to have increased their use of social networks for work (Extract 2) to communicate with students and colleagues during COVID-19, in accord with other professional populations (Pérez-Escoda et al. 2020). Universities had to move teaching to a wholly or partially remote setting, which likely caused and/or increased stress and mental health problems that were already raised due to self-isolation (Yang 2021). Indeed, lockdowns and heavy restrictions impacted the daily life of students and staff worldwide.

The phenomenon is also directly associated by participants with the academic online workload. For example, staff use Twitter, Linkedin, and Facebook to promote their research or stay in touch with other academics (Oksanen et al. 2022). Our results align with recently published papers that emphasised that staff has moved their professional lives online, especially for teaching and meeting with students and colleagues, while further exposing academic staff to potential CB and CS (Oksanen et al. 2022; Watermeyer et al. 2021). Greater access to technology generates/leads to a greater frequency of cyber victimisation. Also, more time spent on social networking sites increases the likelihood of experiencing online harassment from a perpetrator known to the victim (Ramsey et al. 2016).

Academic staff believed that COVID-19 had given perpetrators a reason to contact their former CB and CS victims and that such people used the pandemic as an excuse to return to the conversation because they had more time (Extracts 3 and 4; Fig. 1, Q19:11). During the lockdown, there was less opportunity to follow or see the victims in real life (Fig. 1, Q5:7). It was also more noticeable (from an onlooker’s perspective) since there are fewer people around (Fig. 1, Q5:8).

Ex 3 “I think COVID-19 has given people the reason to contact those they have been cyberstalking. They have used it to re-start up a conversation.” (Staff, female)

Ex 4 “I believe in my circumstance, they have had more time on their hands during lockdowns to think and dwell on things. This has led to more actions on their part.” (Staff, male)

One participant commented that COVID-19 had changed young people’s communication and interaction modalities. Furthermore, perpetrators focused more on digital interactions with their victims (Extract 5). In contrast, some victims reflected that the pandemic had not increased the impact of their experience as victims of CB and CS; however, they reported noticing changes in their social networks and referenced other CB and CS victims during the lockdown (Extract 6). Furthermore, some participants recognised that mental health deteriorated during the worldwide pandemic (Holmes et al. 2020; Wong et al. 2020) and that some disturbing “online” behaviours were not definable or easily misinterpreted (Extract 7).

Ex 5 “Furthermore, COVID-19 has had an impact on young people’s communication and dynamics because online communication has become a norm and their perpetrators direct more attention towards digital interactions with their victims.”(Staff, female)

Ex 6 “I answered that I don’t know because it hasn’t increased for me personally, but I’ve heard about more cases/other victims during the lockdown.” (Staff, male)

Ex 7 “I think the lockdown makes it more difficult to identify cyberstalking from anxious behaviour exhibited by many people online. It seems some don’t know where to draw the line anymore.” (Staff, female)

Students: cyber offenders are more confident and aggressive online, and the victims feel more vulnerable than in the past.

Interestingly, students also commented that it had become easier to communicate aggressively online rather than “face to face”; they feel less responsible and can get away with it (Extract 8; Fig. 1, Q23:10). Perpetrators feel more confident and protected to harass people virtually (Extract 9) (Fig. 1, Q20:11). The pandemic contributed to making the victims more accessible to CB and CS online, and the ‘monitoring’ modalities appear to have intensified (Bracewell et al., 2020). Overall, the COVID-19 epidemic hugely influenced the HE sector worldwide, and students are behind in their learning due to lockdown measures. Students admitted to spending more time online than before (e.g., they enforced online education (Khan 2021), and this factor, according to Barlett et al. (2021), increased cyber offending behaviour.

Ex 8 “People can’t argue things out face to face or figure things out easily. Instead, it has to go online where people can be keyboard warriors and even more malicious than face-to-face because they think they can get away with it if they delete it. Due to COVID, the only way of contacting people is online.” (Student, female)

Ex 9 “Because people feel more confident to be mean behind a screen, and people can easily take photos of you when you’re in zoom calls for lessons.” (Student, female)

Some students highlighted the fear associated with the pandemic, and women especially felt more vulnerable during this period (Extract 10). In effect, the student victims were all female. According to recent literature, young women are likely to become targets of some of the most severe instances of online harassment (Pew Research Center 2021). Also, people from minority backgrounds have been targeted based on their appearance and sexual orientation (Gosse et al. 2021). These findings accord with previous studies showing that online harassment in higher education often targets minority members and women (Oksanen et al. 2022; Yelin and Clancy 2021). In our survey, 73.5% of our participants were female, and we had just three victims from minority groups.

Ex 10 “Yes, Cyberstalking and cyberbullying behaviour increased during COVID-19”. “Women are more scared than ever.” (Student, female)

When we compared personal opinions of students and staff regarding CB and CS, we noticed that staff became more vulnerable cyber aggressions due to an increased use of social channels, MDA and platforms (e.g. MT, Zoom, Twitter and LinkedIn) during the pandemic for activities related to their academic job (e.g. staying in touch/work with other academics and students) (RQ3). These findings also emerged in Oksanen et al.’s (2022) study. Staff in our study explained this increase during the pandemic by citing face-to-face restrictions and “online communication” becoming more of a “norm”. Students also adopted more social channels for academic tasks and staying in touch with friends. However, they highlighted the opportunity for cyber -aggressor’s to hide their behaviours easily “behind the screen”. Both students and staff emphasised that they believe perpetrators of CB and CS became “more confident” to cyberattack their victims. This accords with prior research that found perpetrators felt more confident and protected to harass people virtually during the lockdowns, and the victims were more accessible online (see Bracewell et al. 2020).

Impact of cyberbullying and cyberstalking on the victim (RQ2-RQ3)

Regarding this specific theme, the analysis showed that staff shared more experiences relating to the impact of CB and CS than students. It is possible that, as more mature adults, they were more willing to share their experiences anonymously. All participants referenced the negative impact of CB and CS on their lives. Our research especially highlighted interpersonal and psycho-emotional effects on victims’ lives and the changes they have been forced to implement to protect themselves. It was excruciating for several of the participants, both staff and students, not just being a victim of invasive and aggressive behaviours by the cyber offenders but also having to experience “secondary victimisation” as a direct result of the way institutions have dealt with them (Clemente and Padilla-Racero 2020) (RQ2- RQ3).

Staff: low confidence, feeling guilty and secondary victimisation

The staff mainly reported stress and displeasure because of the institution’s lack of understanding of their situation (RQ2-RQ3). Some staff suffered emotional impact from the cyberbullying/cyberstalking psychological aggressiveness, and they decided to reduce their socialising and ask for medical support for anxiety and depression (Extract 11). These findings also emerged in previous studies (see, e.g. Alsawalqa et al. 2021; Yubero et al. 2017) that showed that cyber aggression lowered victims’ self-esteem and confidence during the pandemic. This negative result was also shown in our research, where victims felt that this experience had destroyed their confidence and self-esteem (Extract 12).

Ex 11 “At times, I was made to feel like I was in the wrong – when I wasn’t – and so another’s reassurance was really important before I accepted that thinking.” (Staff, male)

Ex 12 “It destroyed my confidence. The investigation was awful. I can never meet the investigator again because I felt he didn’t understand the nuances of the situation: he said: “No blame, but you shouldn’t have given her your number...”. He humiliated me in a situation where there was a power-play from the perpetrator already in operation. It was the investigation, not the situation itself, which drove me over the edge.” (Staff, female)

Overall, male staff victims were less worried about the impact of CB and CS in their life and did not feel particularly distressed (Extract 13, Fig. 2, Q25:19). As a more vulnerable target, women may be more conscious of these offences and perceive them as a problem to tackle. A more recent study focusing on allocating blame exhibited significant differences in judgments based on gender, whereby female participants perceived CB and CS as more harmful than males and recommended more severe punishments for perpetrators (Marr and Duell 2021). This aspect is relevant: if the victims do not feel vulnerable but feel self-confident and supported, they can manage CB and CS better. In some cases, our participants were made to feel guilty and co-responsible for the cyber behaviours or humiliated and blamed by the police and misunderstood (Extracts 11 and 12; Fig. 2, Q6:24).

Ex 13 “Whilst I don’t find the cyberstalking particularly distressing, I suspect that is because I do not feel the person is a threat, they are lonely, and despite explaining the reasons they should not contact, they continue to do so. However, I feel that this may provide them with some benefit and doesn’t cause me particular harm other than reducing my use of social media and my willingness to engage with it. (Staff, male).”

We also found that CS and CB forced the participants to change their habits to protect themselves and their personal information (Extract 14). One staff member, a victim of a colleague cyberbully, also experienced a counter allegation for sexual misconduct (Extract 15; Fig. 2, Q28:14- Q28:15). Thus, victims can experience secondary victimisation that can amplify the negative impact on their mental health. Both staff and students have indicated that this issue is problematic and annoying for them (e.g., Yubero et al. 2017). According to Clemente and Padilla-Racero (2020), re-victimisation and secondary victimisation affect mental health. Furthermore, the isolation related to the pandemic lockdown was a significant risk factor for psychological and physical health (Holmes et al. 2020; Das et al. 2020) and determined emotional vulnerabilities, anxiety, and depression (Holmes et al. 2020; Wong et al. 2020).

Cyber victimisation during the pandemic was associated with higher psychological distress and lower self-perceived support and trust. Victims targeted by other members of their university community reported higher PTSD symptoms and a more significant impact of perceived online harassment than other victims (Oksanen et al. 2022). These results are also confirmed in a recent systematic review on CS and cyber-harassment in the general population (Stevens et al. 2021). The research found relevant consequences for the mental health of victims (e.g. depression, anxiety, suicidal ideation and panic attacks).

Ex 14 “The behaviour began when the person was a client of the service I worked for in 2016 and they formed an attachment. They initially tried to find information about me but failed. I had previously been physically stalked, and therefore I have been more protective of my information. They sent me gifts via work, and continue to do so, they send me messages online, and continue to do so. I don’t feel threatened and don’t see the benefit of continuing to challenge it, I just ignore the messages.” (Staff, male)

Ex 15 “I ended up being investigated myself because the bully made an allegation of sexual misconduct against me. I was cleared after a year of hell.” (Staff, female)

Negative emotions and psychological distress

According to recent studies (Peled 2019), the strong negative emotions and psychological distress caused by social networking CB victimisation can influence the academic, social and emotional development of undergraduate students. Furthermore, research by Vranjes et al. (2018) found that feeling sad and afraid in the workplace predicted exposure to CB six months later.

Figure 3 presents an insight into different emotional statuses, scaled from positive emotions (i.e., relieved/ indifferent) to negative emotions (i.e., annoyed/angry; sad/scared/threatened). On the left, frequencies of emotions are presented according to cyber offences. Overall, negative emotions surpass positive emotions, with a higher quota for CS (29.4% against 26.4% for CB). On the right, Fig. 3 shows that staff tended to feel negative emotions more than students. In some cases, staff reported taking antidepressants to manage negative emotions, self-isolating and reducing socialising to protect themselves (Extract 16).

Ex 16 “Went to GP and was put on antidepressants. Cut off all my friends (…) Don’t socialise. Deleted all social media for a few months. Created new social media with only close friends and family. Block any new friend requests I don’t recognise. Don’t interact on public platforms. Changed all passwords. Got a new email account and phone number” (Staff, female).

Fig. 3
figure 3

Emotions: cyber offences, staff and students

Students, often digital natives, may be more able to mitigate psychological distress than staff (RQ3). It is also possible that staff may be more aware of victimisation’s short- and long-term impacts, and their negative emotions may be directly correlated with the perception of the danger faced, especially for cyberstalking. This outcome may also be related to the fact that staff may feel less supported by the institutions as victims. In a previous study published by Bauman and Baldasare (2015), not all students in their sample were equally upset by CB offences. In the present study, respondents experienced a stressful and uncomfortable situation, especially when the cyberbully/cyberstalker was a colleague or were even wrongly blamed for being a victim of a cyber-attack (Yubero et al. 2017).

It emerged that the staff declared more negative strong emotions (e.g. feeling angry, scared, threatened) compared to students, who adopted more neutral/positive emotions (e.g. feeling annoyed, indifferent, fine-relieved) (RQ3). There are several possible explanations for this outcome. Students may be more accustomed to this type of online behaviour by adopting more social networks and consequently more resilient. The “secondary victimisation” reported by staff regarding a lack of understanding and support from formal institutions or trust (e.g. polices forces, managers) may have impacted on their responses (RQ3). Peled (2019) also found that although both groups highlighted the negative impact of CB and CS on their lives, staff reported strong negative emotions and psychological distress (Peled 2019). These findings are also consistent with a recent study on staff, and students indicated that the problem of online harassment is highly prevalent among staff, and very few victims reported the assaults to supervisors or police, which is concerning. The research has also showed that staff victims reported higher PTSD symptoms than other victims (Oksanen et al. 2022). In this regard, Collen et al. (2021) have shown that resilience is a positive mediator in the relationship between cyberbehaviour and psychological well-being. Student resilience protects them from cyberbullying and prevents the impairment of their psychological well-being.


The study presents some potential limitations that merit attention.

  1. 1.

    The small sample size in the study. The topic’s sensitive nature led to the collection of victim experiences through a semi-structured section as part of an online questionnaire. Face-to-face interviews may have posed challenges in people’s willingness to respond openly regarding their experiences while ensuring anonymity.

  2. 2.

    The Ethics Committee at a UK university provided ethical clearance. However, the Committee requested two conditions: to promote the study internally via university channels (e.g., via email, blackboard); to receive departmental approval to involve students as participants. These two understandable restrictions negatively impacted the size of the final sample. This also resulted in some departments not taking part in the study. Compliance with the University Ethics Committee’s requirements limited recruitment to the university and prohibited direct one-to-one approaches to potential participants, which affected research dissemination and reduced the potential participant pool.

  3. 3.

    Participants may have had concerns, especially staff, about completing the questionnaire at the university due to potential recognition. Despite emphasising participant anonymity in the invitation letter and participant information sheet, these concerns may have influenced their decision not to take part.

  4. 4.

    The sample size from a single university presents an explicit limitation; furthermore, it is not certain whether the results are unique to this institution.

  5. 5.

    Regarding the sample, the males were all academic staff members, whereas the students were all females. We can hypothesise that women feel more willing to admit being victims of cyberstalking and cyberbullying, consistent with previous studies (Faucher et al. 2014; Cassidy et al. 2016; 2017).

Conclusions and implications

This paper investigated CB and CS within HE, an under-researched setting (Oksanen et al. 2022; Stevens et al. 2021). To this aim, a convenience sampling technique, through an online semi-structured survey, self-selected academic students and staff who claimed to be victims of these adverse events, during the COVID-19 pandemic. The sensitive nature of the topic posed several challenges to this research. From a methodological perspective, qualitative research proved to be a tool to elicit victims’ perceptions and CS and CB’s impacts (Meter et al. 2021; Harrison et al. 2022). In addition, the qualitative approach provided rich data about victims’ emotions, opinions, vulnerability and behavioural changes, and perceived support mechanisms (RQ1, RQ2).

Most participants, students, and staff, believed cyber behaviours increased during the pandemic (RQ1), which confirms previous research (Barlett et al. 2021; Kaur et al. 2021; Heiman and Olenik-Shemesh 2022). Respondents felt that CB and CS were equally relevant to HE, although CB was perceived as a slightly more common offence. Staff claimed to have augmented the use of social networks for working and communicating with students and colleagues during COVID-19 and directly associated it with their academic online workload. Students (all females) also admitted to spending more time online than before and thus increased their vulnerability (see also Khan 2021). In this explorative study, students appeared more resilient than staff in dealing with adverse cyber events (RQ3). Students coped with stress more effectively and proactively managed negative emotions compared to staff, aligning with previous studies (e.g. Collen et al. 2021).

More research should focus on these two academic groups as victims of CB and CS, their associated risk factors, and psychological and institutional needs (e.g., Oksanen et al. 2022; Alsawalqa et al., 2021). More qualitative research should explore participants’ needs and support mechanisms, and why staff do not feel comfortable reporting cyber aggressions in the academic context. Future research should compare academic and admin staff to deepen our understanding of their needs. Notably, in the present study, only two respondents worked in administration, out of a total of twenty-two staff.

The present findings encourage developing support programs for different groups and implementing effective tools at all levels of the academic community, for coping with online media and exposure and cybervictimisation (Oksanen et al. 2022; Heiman and Olenik-Shemesh 2022).