ISSN: 1550-7521
Muhammad Ali1* and Mehwish Zia2
1PhD student at University of Colorado, Boulder USA
2Riphah International University, Islamabad
Received: 11-Jan-2024; Manuscript No. gmj-24-124926; Editor assigned: 13-Jan- 2024; Preqc No. gmj-24-124926; Reviewed: 22-Jan-2024; QC No. gmj-24-124926; Revised: 27-Jan-2024; Manuscript No. gmj-24-124926 (R); Published: 02-Feb-2024, DOI: 10.36648/1550-7521.22.67.410
Citation: Ali M, Zia M (2024) Engaging Citizens via Twitter: A Comparative Analysis of Social Media Strategies in Community Policing By Greater Manchester Police and Islamabad Capital Territory Police. Global Media Journal, 22:67.
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The widespread acceptance of social media platforms has compelled police departments worldwide to utilize Twitter for community policing. Proponents of this new policing model argue that fostering partnerships between community members and police can strengthen bond between citizens and law enforcement. Community policing necessitates officers to establish direct and close links with public, a task facilitated by Twitter's network-building and one-on-one interaction capabilities. Furthermore, Twitter empowers citizens to voice their opinions on matters of public importance, thereby exercising their democratic rights. Direct communication via Twitter also enables police to consider Citizens feedback when reviewingpolicies,ultimately enhancing their effectiveness.However,the challenge of low online citizen engagement remains. Effective collaboration between citizens and police requires law enforcement agencies to create an environment that encourages increased citizen engagement. This research evaluates the citizen engagement strategies employed by Islamabad Capital Territory Police and the Greater Manchester Police on Twitter. Through a comparative analysis, this study identifies the most commonly used media and content types by both police forces and measures the citizen engagement generated by each. The findings reveal that despite having a larger number of followers and tweets, the citizen engagement generated by GMP on Twitter is relatively low
Social media; Community policing; Citizen engagement; Twitter; Content analysis; Police strategies; Islamabad Capital Territory Police; Greater Manchester Police
The dynamics of police-citizen interactions occasionally lead to undesirable negative experiences, which can significantly impact the relationship between law enforcement and the community. To bridge this gap and foster a more positive connection, community policing has emerged as a vital approach. This model emphasizes the performance of non-enforcement tasks that benefit society, allowing police departments to enhance the citizen-police relationship. By actively considering citizen concerns and incorporating their perspectives, police agencies can review and refine their policies to better align with community expectations. In recent years, social media has emerged as a powerful communication tool [1], prompting police departments to embrace its potential for community policing initiatives.
However, despite the adoption of social media platforms, such as Twitter, as a means of engaging with the community, the challenge of low active online citizen participation persists. This issue necessitates focused attention and strategic solutions.
This research aims to evaluate the Twitter strategies employed by the Islamabad Capital Territory Police (ICTP) and the Greater Manchester Police (GMP) in their community policing efforts. By comparing and contrasting these approaches, this study highlights the media and content types utilized by both police forces. Additionally, it analyzes the levels of citizen engagement generated by each media and content type, offering insights into the overall effectiveness of their Twitter presence. The research also endeavors to identify similarities, differences, and potential best practices.
Community policing
Community policing entails the collaboration between community members and police officials to identify and solve community problems. According to Gowri [2], community policing has been identified as a highly effective new paradigm within the field of policing. According to Wilson and Kelling [3], community policing involves the joint efforts of police and citizens to address the root causes of crime and address community concerns. This methodology has emerged as the prevailing modus operandi of law enforcement on a global scale, encompassing Pakistan as well, and has exerted influence in reconfiguring the dynamics between the state and its citizens [4].
Skogan [5] notes that the Community Policing Consortium (1994) outlines two primary components of community policing, namely Problem-Solving and Community Partnership. The community partnership component places significant emphasis on the imperative for law enforcement agencies to cultivate favorable relationships with the community, concurrently affording community members the opportunity to express their concerns and offer constructive feedback. Police forces, in turn, protect citizens' rights and address problems by attentively addressing community grievances [6]. It is the collective responsibility of all stakeholders concerned with community safety to contribute to its well-being. Through constructive collaboration between the community and the police, public safety can be enhanced. This approach does not alter the underlying objective of law enforcement but instead advocates for the implementation of novel strategies to attain identical objectives [7].
Numerous strategies have been adopted to manage and deter criminal activities, and the effective utilization of social media by law enforcement agencies to bolster community policing has been recognized as one such strategy [8]. With community policing gaining increased attention, efforts are being made to find more effective ways to enhance citizen engagement. Garland [9] suggests that one reason states promote community involvement is to encourage a sense of responsibility among community members. Policies are being developed to foster a community's active participation in achieving goals that were previously considered the sole responsibility of the state. In the case of community policing, the challenge lies in making active citizen involvement a reality [10]. Citizens can help the police by giving information as the eyes and ears of the police due to the limited police resources [11].
Many studies have analyzed how community policing affects public perceptions of law enforcement. For instance, Cordner [12] identified that community policing improved officers' perceptions of the community and their job satisfaction. In addition, police departments frequently solicit community feedback when revising their policies to benefit the neighborhood. However, community policing must be reflected in actions and behaviors to be truly authentic [13].
Citizen engagement
The term "engagement" can vary in meaning depending on the context. Gangi and Wasko [14] describe citizen engagement in the context of social media as a state of mind that allows citizens to become increasingly involved and fulfill their needs.
Involving the public in governmental affairs is not only advised but also seen as a key factor in establishing high-quality governance [15]. The underlying principle of engaging citizens in decisionmaking processes is based on the belief that it is the right and duty of citizens in a democratic country to contribute to shaping the world they live in. The potential for engagement to affect the effectiveness of citizen action has also been argued by theorists. While internet use is not a driving force for engagement, it does facilitate engagement with the community [16]. Gaventa and Barrett [17] contend that active participation by citizens can help achieve governance-related goals but intermediary measures need to be taken to ensure active citizen involvement. Citizen engagement, as defined in this study, refers to the level of involvement and interest shown by citizens in the work of police organizations, specifically through their interactions on Twitter. It aligns with the definition provided by Gangi and Wasko [14]. In the context of this research, citizen engagement is measured by the overall response of citizens on Twitter handles of police forces, which includes actions such as favoriting a tweet, retweeting a tweet, or replying to a tweet. These forms of engagement demonstrate the extent to which citizens are actively interacting and showing interest in the content shared by the police organizations on Twitter.
The selection of GMP and ICTP as the focus of this research is based on several factors: GMP and ICTP are both significant police forces operating in their respective regions. GMP is one of the largest police forces in the UK, serving a diverse and populous area. ICTP is the primary law enforcement agency responsible for maintaining law and order in the capital city of Islamabad, Pakistan. By studying these two police forces, the research aims to gain insights into the strategies and practices of police organizations operating in different contexts. The researchers were able to access the official Twitter accounts of GMP and ICTP, which provided a rich source of data for analysis. The availability of comprehensive and reliable data from these police forces facilitated a detailed examination of their Twitter usage and citizen engagement levels.
Greater Manchester Police's (GMP) social media approach
GMP, the Greater Manchester Police, is the fifth largest police service in the United Kingdom and is responsible for law enforcement tasks within Greater Manchester in North West England. Greater Manchester is one of six metropolitan counties in England, with a population of 2.82 million [18] and covering an area of 493 square miles (1,277 KMs). Use of social media platforms by UK Police unofficially started in 2008 [19]. Research suggests that social media is being utilized by police in the United Kingdom for intelligence gathering, information sharing with police officials and citizens, and citizen engagement [20]. One significant incident that highlighted the potential of social media for police was the London Riots in August 2011. Miscreants involved in the riots used social media to coordinate their activities [21]. In response, police forces started using Facebook and Twitter to share up-to-date information with citizens, resulting in a dramatic increase in Facebook post views and Twitter followers [22]. Intelligence gathered from social media helped track down the perpetrators. Terry Sweeney, Assistant Chief Constable of Greater Manchester Police, acknowledged the role of social media during the crisis, stating that it played an important role in deploying community support [23]. The Home Affairs Committee report recommended that police forces regularly use social media platforms in both conflict and peace situations [23].
Another incident involved GMP conducting an exercise to raise awareness about policing and the time spent on non-crime matter [24]. During this exercise, every event reported to the GMP control room within a 24-hour period was tweeted with the hashtag #gmp24 by three Twitter handles: @gmp24_1, @ gmp24_2, and @gmp24_3. This resulted in a significant increase in followers, from 3,000 to 17,000, demonstrating the positive impact of thoughtful Twitter use by the police [25].
In another incident, two GMP Police Constables, Nicola Hughes and Fiona Bone, were tragically killed on September 18, 2012, in Greater Manchester while responding to a report of burglary. Following this incident, a Twitter campaign using the hashtag #coverforgmp was initiated, and over 2,000 police officials across England volunteered to cover shifts for GMP staff, ensuring they could attend the funerals of their fallen colleagues. YouTube played a crucial role in coordinating the #coverforgmp efforts. Denef S [8] quote Kevin Hoy, the Web Manager of GMP, highlighting how social media campaigns can save money that was previously spent on offline information sharing.
Currently, GMP utilizes various social media platforms including YouTube, Flickr, Pinterest, Instagram, Facebook, and Twitter [26]. The official GMP website enables citizens to find accounts of local officers on Twitter and Facebook. This research focuses specifically on GMP's Twitter presence, and data for analysis was retrieved from their official Twitter handle, @gmpolice, which was created in February 2009 and had 610.8K followers [27].
Islamabad Capital Territory Police's Social Media Approach
The ICTP (Islamabad Capital Territory Police) was established in January 1981 to enforce law and order in the federal capital of Pakistan, Islamabad. Islamabad covers an area of 906 square kilometers, has a population of over 2 million, and boasts a literacy rate of about 88%, the highest in Pakistan [28].
Recognizing the significance of social media in the present age, ICTP made the decision to utilize Facebook and Twitter in January 2014. The objective was to reform the police service by informing citizens about significant incidents and incorporating their recommendations to evaluate progress [29]. Apparently, the department's policy was to inform and involve citizens. However, different sections of the official website were not being regularly updated, and contact details for any official were not mentioned [30]. ICTP Inspector General Tariq Masood Yasin instructed officers to create pages and remain active on social media to bridge the information gap caused by the unavailability of police officials, particularly station in-charges, due to the nature of their job [31]. Some officials even referred to IG ICTP as the "WhatsApp IG" in recognition of his interest in social media [32]. Meanwhile, ICTP continued its efforts to promote friendly relations with citizens through various social activities [33, 34].
Currently, ICTP manages a Facebook page, a Twitter account, and WhatsApp groups. For this research, data was accessed from the official Twitter handle of ICTP, @ICT_Police. The account was created in January 2014 and has 559K followers.
Evidence suggests that community policing positively influences citizens' satisfaction with the police [35]. However, for community policing to yield desired results, a strong bond between citizens and the police is a prerequisite. Increased interaction with citizens, along with the provision of better service, is believed to improve the perception of the police by the people [36]. Twitter provides an opportunity to directly and inexpensively reach citizens, offering greater control over the content's form and theme compared to traditional media [37]. These are some of the reasons why police forces worldwide are utilizing the potential of Twitter for community policing. Lieberman, Koetzle, and Sakiyama [38] emphasize the importance of a proper strategy to determine the type of message being shared and its impact on the community, as negligence in this regard may lead to unforeseen consequences. Hu, Rodgers & Lovrich [39] suggest the need for careful planning of social media strategies, as many police posts fail to engage citizens, and do not have the desired effect.
Statement of the Research Problem
The utilization of Twitter by law enforcement agencies in Pakistan remains an unexplored area in current research. In general, law enforcement agencies commonly utilize social media platforms to disseminate information regarding criminal activities and associated matters. This study aims to evaluate the Twitter strategies of ICTP and GMP in terms of influencing online citizen engagement. It examines the type of content shared by ICTP and GMP to engage with citizens and evaluates the effectiveness of their current Twitter strategies in influencing online citizen engagement. Based on this comparison, the research highlights what generates citizen engagement on Twitter for both police forces.
Research Questions
RQ 1: How are the Twitter handles @gmpolice and @ICT_Police utilized for community policing?
RQ 2: To what extent is the citizen engagement strategy employed by @gmpolice and @ICT Police effective in fostering meaningful interactions with the public?
Advancing the Concept of Social Media Engagement: A Theoretical Framework
The "model of co-creation in the service sector" was introduced by Prahalad and Ramaswamy [40] as a framework for understanding the communication dynamics that occur between users and organizations. Expanding upon the aforementioned model, Gangi and Wasko [14] further developed the theoretical framework by placing emphasis on the social interactions that occur among users of social media within organizational social media platforms. This extension serves to provide a comprehensive explanation for the phenomenon of social media engagement.
The theory of Social Media Engagement centres on the pivotal role that technology plays in facilitating interactions among individuals who are separated by time and space. The concept comprises two primary elements: technical features and social interactions. Social interactions encompass the digital exchanges that occur between individuals utilizing various social media platforms. The derived experience from these interactions encompasses the cultivation of interpersonal connections among users and an examination of the advantages associated with utilizing SM platforms for the purpose of communication. The degree of user engagement on SM platforms is influenced by the interactions among users. Technical aspects, on the other hand, include the functionalities and capacities of the technology that enable these social connections. These features serve as mechanisms that empower users to establish the boundaries and magnitude of their utilization of SM for interpersonal engagements.
Based on the Social Media Engagement theory, it can be posited that heightened levels of user engagement are associated with a corresponding rise in the utilization of the social media platform. Therefore, the frequency of utilization of a social media platform is directly correlated with its increased value in terms of cocreation for both organizations and users.
The research questions were addressed using a quantitative methodology in this study. The data was obtained by extracting tweets from the official Twitter accounts of ICTP and GMP. A content analysis was undertaken in order to gain insight into the utilization of Twitter handles by the ICTP and GMP, with the aim of analyzing the collected data [41]. In order to evaluate the efficacy of the Twitter strategies implemented by the ICTP and GMP, the degree of citizen engagement elicited by their Twitter accounts was quantitatively assessed through indicators such as "replies," "retweets," and "favorites" associated with each tweet. This methodology facilitates a more comprehensive comprehension of the efficacy of Twitter as a mechanism for enhancing community policing by the ICTP and GMP.
Data collection
All tweets available on the ICTP and GMP’s Twitter account between February 1st and April 31st, 2019, covering a three-month period, were collected. The researchers had access to a sufficient number of tweets from both GMP and ICTP during this period, allowing for a meaningful analysis of their Twitter activities and citizen engagement. The sample size of tweets collected (N=203 for ICTP and N=531 for GMP) provides a reasonable dataset for analysis. The dataset included both original tweets and retweets shared on the Twitter handles @ICT_Police and @gmpolice. All tweets were manually downloaded to ensure accurate and reliable data collection. A single tweet was considered as a unit of analysis. Twitter was chosen as the focus of this research due to its widespread usage and its potential for achieving a high level of online citizen engagement. By selecting a specific timeframe and manually collecting the tweets, this data collection method allows for a focused analysis of Twitter usage by the police forces. The selected period captures trends, enabling a comprehensive understanding of the Twitter strategies employed by the ICTP and GMP for community policing during the research period.
Data analysis
Upon manual download of data from the Twitter handles @ICT Police and @gmpolice, the collected data was categorized into two main parts: 'Media Type' and 'Content Type', based on the format and theme of the tweets [42]. Subsequently, a content analysis was conducted, and categories for police tweets were identified through a thorough examination of the data [20] (Table 1).
Categories | Codes |
---|---|
Links | Links with text, videos, photos etc. |
Photos Videos |
Photos uploaded with or without text Videos uploaded with or without text |
Graphics | Graphics (Images only) |
Text | Text only |
Other | Other than the above mentioned |
Table 1: Media Types.
For the 'Media Type' analysis, the data was categorized into the following categories: videos, links, photos, graphics, text, and others. Under the 'Video' category, only tweets that included uploaded videos, with or without accompanying text, were considered. Likewise, tweets containing photos, with or without accompanying text, were classified under the 'Photos' category. Tweets that included links redirecting to videos, photo galleries, news stories, and other external content were categorized as 'Links'. The 'Graphics' category encompassed designed banners that incorporated photos with typography. Tweets without any videos, photos, graphics, or links were grouped under the 'Text' category. Finally, tweets that didn't fit into any of the aforementioned categories, such as screenshots or scanned copies of documents, were assigned to the 'Others' category (Table 2).
Title | Description |
---|---|
Awareness | Online awareness campaigns or content to educate people regarding public safety |
Notifications | Alerts related to new initiatives or guidance etc. |
Appeal for engagement | Content that asked citizens to report a crime or share information etc. |
Achievements | Resolved complaints, solved cases, positive citizen feedback or recognition of police efforts etc. |
Daily affairs of police departments |
Content related to trainings, workshops, seminars, visits, inaugurations, meetings and other activities of police officials. |
Police representation in media | Representation of police officials in newspapers, radio or TV programs etc. |
Community related activities |
Any activity which involved interaction with community members (e.g. events, meetings etc.) |
Statements of police officials |
The official statements of police officials on events, initiatives or meetings etc. |
Special days | Regional, national, international or religious days etc. |
Human interest | Content referring to individuals' interests and emotions. |
Others | Other than the above mentioned. |
Table 2: Content Types.
For the 'Content Type' analysis, the data was categorized into the following categories: police operations, awareness, notifications, appeal for engagement, achievements, daily affairs of police departments, police representation in media, community related activities, statements of police officials, special days, human interest, and others. Under the 'Police Operations' category, tweets containing information related to case proceedings, investigations, arrests, accidents, and other operational activities were included. Tweets aimed at raising awareness or educating the public on topics related to public safety was categorized under 'Awareness'. 'Notifications' encompassed tweets providing alerts about new initiatives or offering guidance. Tweets falling under the 'Appeal for Engagement' category included content that encouraged citizens to report crimes or share information to assist investigations, among other forms of engagement.
'Achievements' included tweets highlighting resolved complaints, solved cases, positive citizen feedback, or recognition of police efforts. In the 'Daily Affairs of Police Departments' category, tweets related to trainings, workshops, seminars, visits, inaugurations, meetings, and other activities involving police officials were included. Tweets specifically focused on police officials' representation in newspapers, radio, TV programs, or other media outlets were categorized under 'Police Representation in Media'. 'Community Related Activities' comprised tweets related to events or initiatives that involved interaction with community members, such as organizing events or conducting meetings. 'Statements of Police Officials' included tweets containing official statements from police officials regarding events, initiatives, or meetings. zTweets referring to regional, national, international, or religious days were grouped under 'Special Days'. Tweets that sparked interest or emotion in individuals, such as humorous content or those related to police dogs and horses, were classified as 'Human Interest'. Tweets that did not fit into any of the above categories were placed in the 'Others' category.
The researchers manually reviewed each tweet to determine its purpose and assigned it to the appropriate category. To ensure accuracy, the categorization process was verified through multiple reviews of all tweets. Finally, the percentage distribution for each category was calculated for comparison.
Citizen engagement
Various metrics have been utilized in research to study citizen engagement via social media platforms, depending on the nature of the study. Lee and Kwak [43] introduced an open government maturity model to investigate public participation through social media in US Federal agencies. Ksiazek TB [44] examined user engagement based on interactivity with online news obtained from social media platforms. Bonsón and Ratkai [42] proposed metrics for evaluating stakeholder engagement on a corporate Facebook page, which were subsequently employed by Bonsón, Royo, and Ratkai [45] to measure citizens' engagement on local government's Facebook pages. These studies highlight the diverse approaches taken to assess and quantify citizen engagement on social media, each tailored to the specific context and objectives of the research (Figure 1).
According to Bonsón and Ratkai [42], citizen engagement on a Facebook page can be assessed by measuring the sum of popularity, commitment, and virality. Specifically, for Facebook, popularity can be determined by calculating the average number of likes per post per 1000 fans, commitment by calculating the average number of comments per post per 1000 fans, and virality by calculating the average number of shares per post per 1000 fans. Bonsón and Ratkai [42] proposed that these metrics could also be applied to measure engagement on other social networking sites, with the function names adjusted accordingly. In this research, the same metrics from Bonsón and Ratkai's [42] Facebook Metrics for Stakeholder Engagement were employed to measure citizen engagement on the Twitter handles. The approach used for Twitter involved calculating popularity as the average number of favorites per post per 1000 followers, commitment as the average number of replies per post per 1000 followers, and virality as the average number of retweets per post per 1000 followers. Table 3 presents the metrics utilized in this research.
Popularity Commitment |
Average no. of favorites per tweet per 1000 fans |
Average no. of replies per tweet per 1000 fans | |
Virility | Average no. of retweets per tweet per 1000 fans |
Citizen Engagement Index of Twitter | Average no. of favorites per tweet per 1000 fans + Average no. of replies per tweet per 1000 fans + Average no. of retweets per tweet per 1000 fans |
Table 3: Citizen Engagement Index of Twitter.
The metrics utilized in this research included the number of followers of each Twitter account to measure popularity, commitment, and virality. This approach ensured that the metrics were independent of the size of the audience. By applying these metrics, the Citizen Engagement Index for both ICTP and GMP was calculated and compared for both the 'Media' and 'Content' types.
Findings
This section is divided into two parts. The first part provides an overview of the Twitter usage by ICTP and GMP, focusing on the 'Media' and 'Content' types. It explores how these police forces utilize Twitter for communication and content dissemination. The second part presents the overall citizen engagement index, which measures the level of citizen engagement on Twitter for both police forces.
Twitter Use of ICTP & GMP
The findings indicate that during the three-month period from February to April 2019, ICTP posted a total of N=203 tweets, while GMP posted a higher number of tweets with a total of N=531.
Media Type. Table 4 and 5 present a comprehensive breakdown of the Twitter usage by ICTP and GMP, respectively, categorized according to the 'Media' type of their tweets.
Category | Description | Apr-19 | Mar-19 | Feb-19 | Total | Percentage |
---|---|---|---|---|---|---|
Videos | Video uploaded with or without text | 14 | 12 | 13 | 39 | 19.21% |
Links | Links with text, videos, photos etc. | 0 | 1 | 0 | 1 | 0.49% |
Photos | Photos uploaded with or without text | 42 | 19 | 21 | 82 | 40.39% |
Graphics | Graphics (Images only) | 20 | 30 | 18 | 68 | 33.50% |
Text | Text only | 2 | 1 | 0 | 3 | 1.48% |
Others | Other than the above mentioned | 3 | 2 | 5 | 10 | 4.93% |
Total | 81 | 65 | 57 | 203 | 100.00% |
Table 4: ICTP: Media Type.
Category | Description | Apr-19 | Mar-19 | Feb-19 | Total | Percentage |
---|---|---|---|---|---|---|
Videos | Video uploaded with or without text | 3 | 4 | 1 | 8 | 1.51% |
Links | Links with text, videos, photos etc. | 116 | 150 | 139 | 405 | 76.27% |
Photos | Photos uploaded with or without text | 15 | 29 | 14 | 58 | 10.92% |
Graphics | Graphics (Images only) | 11 | 18 | 9 | 38 | 7.16% |
Text | Text only | 5 | 5 | 12 | 22 | 4.14% |
Others | Other than the above mentioned | 0 | 0 | 0 | 0 | 0% |
Total | 150 | 206 | 175 | 531 | 100.00% |
Table 5: GMP: Media Type.
When analyzing the 'Media' type of ICTP & GMP tweets, it was found that the majority (40.39%) of ICTP's tweets consisted of photos. Graphics accounted for the second largest portion (33.50%) of their tweets, followed by videos at 19.21%. Only a small percentage (0.49%) of ICTP's tweets included links redirecting to videos, photo galleries, or news stories. In contrast, the majority (76.27%) of GMP's tweets contained links. Photos constituted the second largest category (10.92%) of GMP's tweets, while videos made up only 1.51%. ICTP's tweets that included screenshots of feedback and documents accounted for 4.93% of their total tweets, while none of GMP's tweets fell into this category or any other miscellaneous media category. Only 1.48% of ICTP's tweets consisted solely of text. GMP had 4.14% of tweets containing only text and 7.16% of tweets containing graphics.
Content type: Table 6 and 7 present the comprehensive analysis of ICTP and GMP's Twitter activity based on the 'Content Type’ of their tweets.
Category | Description | Apr-19 | Mar-19 | Feb-19 | Total | Percentage |
---|---|---|---|---|---|---|
Police Operations | Updates related to proceedings of cases, investigations, arrests, accidents and operations etc. | 20 | 9 | 7 | 36 | 17.73% |
Awareness | Online awareness campaigns or content to educate people regarding public safety | 2 | 7 | 2 | 11 | 5.41% |
Notifications | Alerts related to new initiatives or guidance etc. | 3 | 11 | 11 | 25 | 12.31% |
Appeal for Engagement | Content that asked citizens to report a crime or share information etc. | 1 | 4 | 8 | 13 | 6.40% |
Achievements | Resolved complaints, solved cases, positive citizen feedback or recognition of police efforts etc. | 6 | 2 | 1 | 9 | 4.43% |
Daily affairs of Police Departments | Content related to trainings, workshops, seminars, visits, inaugurations, meetings and other activities of police officials | 21 | 10 | 9 | 40 | 19.70% |
Police Representation in Media | Representation of police officials in newspapers, radio or TV programs etc. | 0 | 0 | 0 | 0 | 0.00% |
Community Related Activities | Any activity which involved interaction with community members (e.g. Events, meetings etc.) | 17 | 12 | 14 | 43 | 21.18% |
Statements of Police Officials | The official statements of police officials on events, initiatives or meetings etc. | 1 | 2 | 1 | 4 | 1.97% |
Special Days | Regional, National, International or Religious days etc. | 2 | 3 | 1 | 6 | 2.95% |
Human Interest | Content referring to individuals' interests and emotions | 0 | 0 | 0 | 0 | 0% |
Others | Other than the above mentioned | 8 | 5 | 3 | 16 | 7.88% |
Total | 81 | 65 | 57 | 203 | 99.96% |
Table 6: ICTP: Content Type.
Category | Description | Apr-19 | Mar-19 | Feb-19 | Total | Percentage |
---|---|---|---|---|---|---|
Police Operations | Updates related to proceedings of cases, investigations, arrests, accidents and operations etc | 47 | 68 | 74 | 189 | 35.59% |
Awareness | Online awareness campaigns or content to educate people regarding public safety | 7 | 12 | 5 | 24 | 4.51% |
Notifications | Alerts related to new initiatives or guidance etc | 6 | 9 | 10 | 25 | 4.70% |
Appeal for Engagement |
Content that asked citizens to report a crime or share information etc | 57 | 69 | 61 | 187 | 35.20% |
Achievements | Resolved complaints, solved cases, positive citizen feedback or recognition of police efforts etc | 6 | 8 | 3 | 17 | 3.20% |
Police Representation in Media |
Representation of police officials in newspapers, radio or TV programs etc | 6 | 3 | 6 | 15 | 2.82% |
Community Related Activities | Any activity which involved interaction with community members (e.g. Events, meetings etc.) | 2 | 1 | 1 | 4 | 0.75% |
Statements of Police Officials |
The official statements of police officials on events, initiatives or meetings etc. | 3 | 8 | 2 | 13 | 2.44% |
Special Days | Regional, National, International or Religious days etc. | 2 | 3 | 2 | 7 | 1.31% |
Human Interest | Content referring to individuals' interests and emotions | 9 | 7 | 4 | 20 | 3.76% |
Others | Other than the above mentioned | 5 | 16 | 5 | 26 | 4.89% |
Total | 150 | 206 | 175 | 531 | 99.92% |
Table 7: GMP: Content Type.
For ICTP, the highest percentage of tweets (21.18%) fell under the category of 'Community Related Activities', involving interactions between ICTP officials and members of the community. In contrast, only 0.75% of GMP tweets were related to community activities. The second highest percentage of ICTP tweets (19.70%) focused on the 'Daily Affairs of ICTP Department', including visits, trainings, seminars, meetings of police officials. The percentage of GMP tweets in this category was also 0.75%. Regarding police operations, the highest percentage of GMP tweets (35.59%) provided updates and information related to ongoing cases, investigations, arrests, accidents, and other operations. In comparison, 17.73% of ICTP tweets fell into this category. The second highest percentage of GMP tweets (35.20%) belonged to the 'Appeal for Engagement' category, which included content asking citizens to report crimes or share information. In contrast, only 6.40% of ICTP tweets were classified under this category. For GMP, 3.76% of tweets fell under the category of 'Human Interest', featuring photos of police dogs and horses, event photo galleries, and content related to football matches. None of the ICTP tweets were included in this category. Additionally, 2.82% of GMP tweets fell under 'Police Representation in Media', which specifically showcased the representation of GMP officials in newspapers, radio, or TV programs. Although there were ICTP tweets related to media coverage of police operations, none of them fit into the category of 'Police Representation in Media'.
The percentages of ICTP and GMP tweets categorized as 'Awareness' were 5.41% and 4.51%, respectively. 'Notifications' accounted for 12.31% of ICTP tweets and 4.70% of GMP tweets.
'Achievements' constituted 4.43% of ICTP tweets and 3.20% of GMP tweets. Statements from police officials were present in 1.97% of ICTP tweets and 2.44% of GMP tweets. The percentages of ICTP and GMP tweets related to 'Special Days' were 2.95% and 1.31%, respectively. 'Others' category encompassed 7.88% of ICTP tweets and 4.89% of GMP tweets.
ICTP tweets in this category mainly covered content related to funerals and police in action deaths, while GMP tweets were primarily tributes paid to victims by their families.
Citizen Engagement Index of Twitter
Media type: Table 8 and 9 present the citizen engagement index of ICTP and GMP based on Media Type. These tables provide insights into the level of citizen engagement generated by each police force on Twitter, categorized by the type of media used in their tweets.
Media Type | Popularity | Commitment | Virality | Engagement |
---|---|---|---|---|
Videos | 6.029 | 0.397 | 1.557 | 7.983 |
Links | 1.701 | 0.07 | 0.354 | 2.125 |
Photos | 2.116 | 0.179 | 0.286 | 2.581 |
Graphics | 1.354 | 0.129 | 0.34 | 1.823 |
Text | 9.12 | 0.85 | 1.996 | 11.966 |
Others | 1.279 | 0.138 | 0.467 | 1.884 |
Table 8: ICTP: Citizen Engagement- Media Type.
Media Type | Popularity | Commitment | Virality | Engagement |
---|---|---|---|---|
Videos | 0.348 | 0.026 | 0.727 | 1.101 |
Links | 0.06 | 0.008 | 0.04 | 0.108 |
Photos | 0.302 | 0.019 | 0.053 | 0.374 |
Graphics | 0.206 | 0.0118 | 0.054 | 0.2718 |
Text | 0.095 | 0.0135 | 0.0226 | 0.1311 |
Others | 0 | 0 | 0 | 0 |
Table 9: GMP: Citizen Engagement- Media Type.
According to the research findings, the highest level of citizen engagement among ICTP tweets is observed in the 'Text' category, accounting for 42% of the overall engagement. On the other hand, the 'Graphics' category exhibits the lowest level of citizen engagement, with only 6% of engagement. For GMP, the 'Videos' category generates the highest level of engagement at 35%, while the 'Links' category generates the lowest level of engagement at 5%. It is important to note that none of the GMP tweets fall under the 'Others' media type, resulting in a '0' engagement for this category.
Content Type: Table 10 and 11 provide an analysis of the citizen engagement levels of ICTP and GMP based on Content Type. The research findings indicate that for ICTP, the content type 'Others' generated the highest level of engagement at 31%, while the content type 'Special Days' had the lowest engagement level at 3%. It is worth noting that the content types 'Human Interest' and 'Police Representation in Media' did not generate any engagement as none of the ICTP tweets fell into these categories. On the other hand, for GMP, the content types 'Notifications' and 'Others' had the highest level of engagement at 24%, while the content types 'Police Representation in Media' and 'Community Related Activities' had the lowest engagement levels at 2% and 1% respectively. The content types 'Awareness' and 'Police Operations' of ICTP tweets exhibited the second highest level of engagement.
Categories | Popularity | Commitment | Virility | Engagement |
---|---|---|---|---|
Police Operations | 3.22 | 0.279 | 0.856 | 4.355 |
Awareness | 3.39 | 0.183 | 1.478 | 5.051 |
Notifications | 2.283 | 0.182 | 0.547 | 3.012 |
Appeal for engagement | 1.06 | 0.109 | 0.321 | 1.49 |
Achievements | 2.256 | 0.216 | 0.322 | 2.794 |
Daily affairs of police departments | 2.591 | 0.178 | 0.36 | 3.129 |
Police representation in Media | 0 | 0 | 0 | 0 |
Community related activities | 1.191 | 0.08 | 0.193 | 1.464 |
Statements of police officials | 1.426 | 0.115 | 0.256 | 1.797 |
Special Days | 0.856 | 0.0413 | 0.189 | 1.0863 |
Human Interest | 0 | 0 | 0 | 0 |
Others | 8.3 | 0.728 | 1.603 | 10.631 |
Table 10: ICTP: Citizens Engagement - Content Type.
Category |
Popularity | Commitment | Virality | Engagement |
---|---|---|---|---|
Police Operations | 0.074 | 0.0115 | 0.019 | 0.1045 |
Awareness | 0.058 | 0.015 | 0.0311 | 0.1041 |
Notifications | 0.381 | 0.023 | 0.25 | 0.654 |
Appeal for engagement | 0.017 | 0.0032 | 0.037 | 0.0572 |
Achievements | 0.275 | 0.0092 | 0.03 | 0.3142 |
Daily affairs of police departments | 0.148 | 0.0219 | 0.032 | 0.2019 |
Police representation in Media | 0.048 | 0.0041 | 0.0126 | 0.0647 |
Community related activities | 0.0172 | 0.0038 | 0.0059 | 0.0269 |
Statements of police officials | 0.105 | 0.021 | 0.038 | 0.164 |
Special Days | 0.133 | 0.01 | 0.023 | 0.166 |
Human Interest | 0.18 | 0.013 | 0.023 | 0.216 |
Others | 0.369 | 0.022 | 0.271 | 0.662 |
Total | 0.102 | 0.01 | 0.05 | 0.162 |
Table 11: GMP: Citizens Engagement - Content Type.
Based on the research findings presented in Table 12 and 13, it is evident that despite having a larger reach and a higher number of tweets, the overall citizen engagement level of GMP is lower compared to ICTP.
Popularity | Total no. of tweets |
Total favorites | P2= Totals favorites/ total no. of tweets |
P3= (P2/no. of fans)X 1000 |
---|---|---|---|---|
203 | 15313 | 75.43 | 2.673 | |
Commitment | Total no. of tweets |
Total replies | C2= Total replies/total no. of tweets |
C3= (C2/no. of fans)X 1000 |
203 | 1213 | 5.97 | 0.211 | |
Virility | Total no. of tweets |
Total retweets | V2= Totals retweets/total no. of tweets |
V3=(V2/no. of fans)X 1000 |
203 | 3342 | 16.46 | 0.583 | |
Popularity | Commitment | Virility | Engagement | |
Total | 2.673 | 0.211 | 0.583 | 3.467 |
Table 12: ICTP: Total Citizen Engagement.
Popularity | Total no. of tweets |
Total favorites | P2= Totals favorites/total no. of tweets |
P3= (P2/no. of fans)X 1000 |
---|---|---|---|---|
531 | 31731 | 59.75 | 0.102 | |
Commitment Total no. of tweets |
Total replies | C2=Total replies/total no. of tweets |
C3= (C2/no. of fans)X 1000 |
|
531 | 3100 | 5.83 | 0.01 | |
Virility | Total no. of tweets |
Total retweets | V2= Totals retweets/total no. of tweets |
V3= (V2/no. of fans)X 1000 |
531 | 16094 | 30.3 | 0.05 | |
Popularity | Commitment | Virility | Engagement | |
Total | 0.102 | 0.01 | 0.05 | 0.162 |
Table 13: GMP: Total Citizen Engagement.
The aim of this research was to analyze the strategies of ICTP and GMP for citizen engagement on Twitter and to examine the level of citizen engagement generated by their tweets. The analysis of Twitter usage based on 'Media' type revealed that both ICTP and GMP utilized a variety of media types in their tweets [46- 51]. Photos and graphics were the dominant media types for ICTP, whereas GMP primarily shared tweets with links. ICTP had a higher percentage of video content as compared to GMP, and a small portion of their tweets included screenshots. The analysis also showed that despite the higher number of GMP tweets, the engagement levels varied across different media types. Textbased tweets generated the highest engagement for ICTP, while videos generated the highest engagement for GMP.
The analysis of Twitter usage based on 'Content' type highlighted notable differences between ICTP and GMP. ICTP tweets primarily focused on community-related activities and the daily affairs of police departments, while GMP tweets predominantly revolved around police operations and appeals for citizen engagement. GMP also had a significant number of tweets related to police representation in media and human interest stories, which were absent in the ICTP tweets.
The examination of citizen engagement based on 'Content' type revealed that ICTP tweets related to community activities had low engagement despite being the most frequently shared content. GMP tweets related to police operations and awareness campaigns generated low engagement, whereas tweets related to tribute or in service death of police officials garnered notable engagement for both police forces.
Overall, the findings suggest that despite the higher reach and number of tweets by GMP, ICTP achieved a higher level of citizen engagement. This indicates that the nature of tweets plays a crucial role in generating engagement rather than sheer quantity. Videos and content that showcase the sacrifices of police officials or stories of victims tend to generate higher engagement. Human interest stories related to police officials or departments also have the potential to engage citizens by providing a glimpse into the human side of policing.
Limitations
Although the sample size was sufficient for exploring the research topic, a larger dataset would have allowed for more in-depth analysis. Additionally, the exclusion of subjective feedback from citizens, such as replies to each tweet, limited the comprehensive evaluation of the effectiveness of the police Twitter strategy. Future research could consider incorporating subjective feedback to gain a more holistic understanding of citizen engagement.
The research findings are specific to the Twitter accounts of ICTP and GMP during the specified time period. These findings may not be generalizable to other police forces or different time periods. It is important to consider the context and specific characteristics of each police force when interpreting the results.
Future research
Based on the current research, there are several areas that could be explored in future studies to further enhance our understanding of citizen engagement on social media platforms like Twitter. Firstly, conducting a longitudinal study that spans a longer period of time would provide a more comprehensive analysis of the trends and patterns in citizen engagement. By examining the changes in engagement levels over time, researchers can gain insights into the long-term effectiveness of Twitter strategies employed by police forces and identify any evolving citizen preferences or engagement dynamics. Secondly, comparing the Twitter strategies and citizen engagement levels of multiple police forces or organizations operating in different regions or countries could offer valuable insights into the factors that influence successful citizen engagement. By examining the similarities and differences in strategies, content types, and engagement levels, researchers can identify best practices and determine the contextual factors that contribute to effective engagement. Thirdly, expanding the research to include other social media platforms, such as Facebook or Instagram, would allow for a comparative analysis of citizen engagement across different platforms. This would provide a more holistic understanding of the strengths and weaknesses of each platform and enable police forces to tailor their strategies to the specific characteristics and audience preferences of each platform.
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