The Use of Social Network in Enhancing E-Rulemaking Lobna Sameer, Hany Abdelghaffar German University in Cairo, Cairo, Egypt.
[email protected] [email protected] Abstract E-rulemaking is concerned with the use of ICTs to allow citizens to read the laws the government is working on, and submit their feedback so this feedback can be incorporated in the finalized laws. Forums have been the main technological tool used in e-rulemaking however they have shown many limitations, and are unable to fulfill all the requirements of e-rulemaking. It is thought that the use of social networks in e-rulemaking might remedy these limitations as SNSs showed a political impact in other political activism venues. However, little research has been conducted to investigate the use of SNSs in e-rulemaking. This research answers the following research question “How can social networks be used in enhancing e-rulemaking?” To answer this question, a proposed conceptual model and a research model were developed and tested through qualitative and quantitative methods. Five out of the variables studied (information collection, user interface, privacy, security, and use of emoticons in communications) were found to have a significant influence over citizen inclusion in e-rulemaking. Accordingly the research contributed the determination of the variables that influence the use of SNSs in e-rulemaking. Moreover, the research contributes a conceptual and a research model illustrating the effect of these variables on e-rulemaking as well as an understanding of how social networking sites could be used to enhance e-rulemaking practices and citizen inclusion Keywords: social networks, social media, e-rulemaking, e-participation, inclusion
1. Introduction Electronic rulemaking allows citizens to use ICTs to read the regulations proposed by governmental agencies, and provide their feedback on them. It increases the participation of those that have not been engaged in the rulemaking process (Emery and Emery, 2005; Beierle, 2003). Representative deliberations on forums are considered the only method by which governmental agencies seek out a public opinion on the rules they are developing (Coglianese, 2011; Schlosberg et al, 2009; Benjamin, 2006; Weeks, 2000). However, such forums are complicated and do not fulfill the requirements of erulemaking (Schlosberg et al, 2008; Benjamin, 2006). Governmental agencies are contemplating the use of new technologies to improve the quality of such deliberations (Coglianese, 2011; Farina, 2010; Schlosberg et al, 2008; Benjamin, 2006; Coglianese, 2004). Unfortunately, little research has been done to examine how an SNS can be used in e-rulemaking. This paper is presenting a model of how SNSs can enhance e-rulemaking. It aims at answering the following research question: “How can social networks enhance e-rulemaking?” The paper starts by presenting the theoretical background for understanding e-rulemaking followed by the proposed e-rulemaking model, research methodology and discussing the findings.
2. Theoretical background 2.1 The E-rulemaking process The rules’ development process differs between agencies inside the same country, and across countries (Schlosberg et al, 2008). The rulemaking process in many countries is still solely executed by officials and does not directly involve citizens. Allowing citizens to comment on the regulations that are to govern them would help ensure the well being of democracy in many countries. Hence, electronic rulemaking has the potential to improve the rulemaking process, increase citizen engagement, and improve the quality of issued rules (De Figueiredo, 2006; Shulman, 2005). The erulemaking process followed in the United States through forums illustrated in figure (1). Is an example of such a process and is going to be adopted in this research.
Figure (1): E-Rulemaking process in the USA
2.2 Democratic deliberation theory and e-rulemaking E-rulemaking requires agencies to publish the rules they are developing, and to collect, and respond to, the feedback they receive when finally the rule (Schlosberg et al, 2008; De Figueiredo, 2006). Agencies can fulfill this obligation through democratic deliberations (Beierle, 2003; Weeks, 2000). Deliberative democracy theory believes that; informed voluntary citizens’ discussions of the issues that concern them help the government in decision making (Schlosberg et al, 2008; Ranerup, 2000). Thus, a democratic practice like e-rulemaking should rely on the study of citizens’ online and/or offline deliberations (Min, 2007; De Figueiredo, 2006). The deliberation model by Perote-Pena and Piggins (2012) in figure (2) is a generic model that can be modified to fit e-rulemaking deliberations. It has five stages after which a social choice is reached. In adopting this model in this research; the voting stage will be removed, as the main aim of e-rulemaking is to discover new issues that the government did not consider while rulemaking and not the conduct of a vote to pass/reject a rule, the main deliberation variables that are thought to affect e-rulemaking are discussed next.
Pre deliberation preference
Deliberation process
Post deliberation preference
Voting rule
Social choice
Figure (2): Deliberation model by Perote-Pena & Piggins (2012) Information management: divided into information provision and collection. Information provision requires that information should be provided to citizens, as an informed citizen is the base of deliberations (Bertot, 2012; Farina, 2010; Schlosberg et al, 2008). SNSs aid in creating informed citizens (Schlosberg et al, 2008; Min, 2007) as they allow access to information without gatekeepers (Bertot, 2012; Oehri and Teufel, 2012; Iskander, 2011). On the other hand, SNSs allow data mining which saves the agencies money and improves the quality of data analysis (Kuzma, 2011; Coglianese, 2003). Agencies should emphasize that the quality of comments received matter more than their quantity (De Figueiredo, 2006; Farina, 2010), as rule makers are mainly interested in receiving new information that would help them improve the proposals they are working on (Shulman, 2009; Emery and Emery, 2005). Based on this we assume the following two hypotheses: H1: Information provision through SNSs significantly Influences citizen inclusion in of e-rulemaking H2: Information collection through SNSs significantly Influences citizen inclusion in e-rulemaking
2.3 Social networking sites (SNSs) Social Networking Sites (SNSs) are web services that allow users to create profiles, interact and share information with others (Bertot, 2012; Oehri and Teufel, 2012; Burke et al, 2011; Kuzma, 2011; li et al, 2011; Wilson et al, 2009). SNSs created a communication channel between citizens and activists that was not present before. (Choudhargy et al, 2012; Sundaram et al, 2012) and has become the study interest of many researchers in information systems, and political sciences (Abdelghafar and Sameer, 2013; Lim, 2008). SNSs were utilized in the 2008 American presidential elections (Bertot, 2012) and in the Egyptian and Tunisian revolutions in 2011 and 2010 (Abdelghafar and Sameer, 2013; Choudhargy et al, 2012; Iskander 2011). According to Papacharissi (2009), what makes some SNSs more successful than others is the unique combination of their features. There features and combinations would affect the use of SNSs in rulemaking and are thus studied next. A. The user interface: A graphical link between a system and the user (Nasir, 2010). If the interface of an SNS is hard to understand, the users might choose not to use the SNS at all (Gross and Acquisti, 2005); which defeats the purpose of these networks. The government should consider the capabilities of the citizens and the interface of the SNS to be selected for rulemaking amd to find a balance (Crespo, 2013; Nasir, 2010). A deliberation tool should have an interface that is easy to use to encourage participation (Yetim 2009). Based on this we hypothesize: H3: The user interface of SNSs significantly Influences citizen inclusion in e-rulemaking B. Communication methods: SNSs support almost all kinds of communications although text communications dominate (Chandramouli, 2011); however, text communications seem lacking in emotional expression (Schlosberg et al, 2008). Multimedia and emoticons give the users more expression tools (Bertot, 2012). However collection and analysis of multimedia requires resources from the government which might not be available (Shulman 2009). Some researchers believe that the lack of emotions makes deliberation objective, and encourages inclusion of minorities (Min, 2007). Others believe that multimedia and emoticons make discussions as natural as possible (Yetim 2009).
The government thus has the choice of allowing or prohibiting multimedia depending on its available resources and the abilities of the involved stakeholders. Based on this we assume the following; H4: Multimedia communications on the SNS significantly Influences citizen inclusion in e-rulemaking H5: Emoticons Communication on the SNS significantly Influences citizen inclusion in e-rulemaking C. Privacy: Methods of access to private information by members and non-members of the network are defined in the early stages of SNS technical design (Boyd and Heer, 2006). A study conducted revealed that most of the SNSs have privacy policies protecting their users (Kuzma, 2011). Regardless, members might use third party applications that could access their information with or without their permission (Oehri and Teufel, 2012). Researchers however believe that privacy violations are a price of living in the digital age and cannot be totally avoided (Laudon et al, 2013; Oehri and Teufel, 2012; Kuzma, 2011). Based on this we assume the following; H6: The privacy options of the SNS significantly Influences citizen inclusion in e-rulemaking
2.4 Environmental influences on e-rulemaking These are deliberation and technological variables that are outside the direct manipulation of the government and thus were classified together in a separate category. These variables are A. Security: One of the issues of e-rulemaking is the security of confidential information (Coglianese, 2003). Other issues include denial of service attacks, phishing, viruses, spyware, and Trojans. These attacks can be avoided through different technological methods; however they remain a threat (Chandramouli, 2011). Reaching a 100% secure SNS is impossible and is not cost effective thus governmental agencies should accept a certain degree of security threats in the SNS they wish to use (Oehri and Teufel, 2012). Based on this we assume the following; H7: The Security level of the SNS significantly Influences citizen inclusion in e-rulemaking B. Interest Groups: They utilize technologies to mobilize individuals and generate comments on rule proposals (De Figueiredo, 2006; Shulman, 2009) thus ineffectively increasing the analysis cost. The government has to emphasize that what matters is the value the comments add to rulemaking and not their quantity (Shulman, 2009). The government could also encourage interest groups to submit a single comment with signatures attached to it (Emery and Emery, 2005). On the other side, some researchers believe that these campaigns could be a fire alarm to the consequences a new rule might bring (Shulman, 2009). Based on this we assume the following; H8: interest groups on the SNS can significantly Influences citizen inclusion in e-rulemaking
3. Proposed model The proposed model was developed by matching the adopted deliberation model to the e-rulemaking process. The variables thought to affect e-rulemaking in table (1) were added to the model. The outcome of e-rulemaking is measured through the increase in the willingness of those that have not been previously engaged in e-rulemaking to engage in e-rulemaking in the future. Table (1): Variables included in the proposed conceptual model
2. Technological variables
1. Deliberation variables
Variables
Measuring factor •
1.1 • Information Management
2.1 user interface
•
Information provision Information collection User Interface
2.2 Communicati on method
Multimedia
2.3 Privacy •
Data protection
Emoticons
Definition Perceived readiness of the government to publish and erulemaking information
Source Bertot, 2012; Chandramouli, 2011; Schlosberg et al, 2008
Perceived readiness of the government to collect citizen comments for analysis The user evaluation of the layout of the tool that is to be used in erulemaking
Kuzma, 2011; Farina, 2010; Barnes, 2006; Shulman, 2005;
The use of multimedia in deliberations The use of pectoral representation of emotions in deliberations
Bertot, 2012; Chandramouli, 2011; Coglianese, 2003. Schlosberg et al, 2008; boyd and Heer, 2006; Laudon et al, 2013; Oehri and Teufel, 2012; Kuzma, 2011; Papachaissi, 2009.
Perceived protection of confidential data
Laudon et al, 2013; Asur and Huberman, 2010; Nasir, 2010
3. Environmenta l variables
•
Vulnerability to attacks
Perceived ability of the tool to withstand outside attacks
Oehri and Teufel, 2012; Chandramouli, 2011; Papachaissi, 2009;
3.2 Influence• groups
Influence of interest groups
Perceived ability of interest groups to mobilize citizens
sur et al, 2010; Shulman, 2009; Schlosberg et al, 2008; De Figueiredo, 2006;
3.1 Security
To validate the proposed model, two interviews were conducted; the first with an expert in information system, the second with a legislation expert. The proposed model was presented to them, and they were encouraged to give their feedback. The improved conceptual model is in figure (3).
Figure (3): Improved proposed conceptual model
4. Research methodology Egypt was selected to answer the research question of “how can social networks enhance erulemaking?” because SNSs have become an activism channel for the Egyptian youth. This has been clear in revolution of 2011 (Iskander, 2011). Accordingly, it could be assumed that the use of SNSs in e-rulemaking would increase the inclusion of some sectors of the Egyptian society in rulemaking. An exploratory research deign was employed as little is known about the phenomena understudy (Saunders et al, 2012; Sekaran and Bougie, 2010). Combinations of quantitative and qualitative data collection methods have been used in this research. The use of a combination of different data collection methods help overcome some of the limitations singular data collection methods (Sekaran and Bougie, 2010). The research process is presented in figure (4):
Figure (4): Research process
Prototype development and pilot study a prototype was developed on Facebook as it has the highest reach in the Egyptian society (Abdelghafar and Sameer, 2013; Arab media outlook, 2012), It has a simple interface, supports communications in multimedia and emoticons, has a privacy policy, a known level of security (Papacharissi, 2009; Boyd and Ellison, 2008; Gross and Acquisti, 2005) and most of the influence groups in Egypt have a presence on it (Iskander, 2011). A pilot study was conducted to evaluate the developed questionnaire and interviewer’s guide. Fifteen scholars in the fields of information systems and management used the prototype, filled in the questionnaire and their feedback was used in the improvement of the prototype and questionnaire. Some scholars went through a pilot interview and their feedback was used in improving the interviewer’s guide. Statistical tests were run to ensure the validity of the questionnaire. The Cronbach Alpha of the different sections of the questionnaire ranged from 0.68 to 0.80. A valid questionnaire should not have a Cronbach Alpha of less than 0.7 (IBM, 2011). The results indicate a moderate to good validity level. Questionnaires design Questionnaires were used as they are precise, quick, and reach a wider spectrum of participants (Blumberg et al, 2008; Ghauri, and Gronhaug, 2005). The questionnaires were developed by the researcher based on the literature review and the improved conceptual model. The population of the questionnaire included Egyptian politically active social networks users above the age of eighteen. Two hundred and eighty six participants successfully completed the study reached through Facebook through purposeful sampling. The questionnaire has five sections including sections for the measured variables, and demographic data. Descriptive analysis summarized the results of the demographic data and the results are in table (2). Table (2): Demographic Data summary Variable Gender
Age
Frequency of social networks usage
Social Networks used
Male Female Less than 18 19 to 29 30 to 40 41 to 51 Above 51 Daily Weekly Monthly Facebook Twitter Google+ MySpace
Number 107 179 0 168 77 20 20 289 16 1 297 166 52 3
Percentage 37% 62% 0% 58% 26% 7% 7% 94% 5.6% 0.4% 57% 31% 13% 1%
Expert Interviews design Semi-structured interviews allow for in-depth understanding of the issues at hand (Saunders et al, 2012; Sekaran and Bougie, 2010). Purposeful sampling was employed as it allows the researcher to choose the sample based on their professional judgment (Saunders et al, 2012). It is appropriate for this research as the researcher wishes to interview the middle level managers who are involved in erulemaking, as those are the managers with the most relevant experience to the phenomenon understudy. Two middle level governmental managers at the Egyptian Ministry of State and Administrative Development (MSAD) were interviewed to validate the developed mode.
5. Analysis and results 5.1 Interviews results The interviewed sample believed it essential to provide citizens with information about the rules the government wants to issue and to collect their feedback on it. As for the technological variables; the interviewees believed that the user interface of an e-rulemaking tool should be easy to understand. Allowing multimedia could be a good feature; however, there are concerns on the analysis of such content. Multimedia analysis would add more costs to the government. The same applies to the use of emoticons in communications. In addition to that, it is important to maintain privacy for both the government and citizens. As for the environmental variables; the Interviewed sample communicated that certain influence groups can have greater mobilization abilities online than others. Some users
might create multiple accounts to submit variations of the same comments. The interviewees believe that security is an external issue that would remain a thread to all online mediums of communications. Violations cannot be completely eliminated and must be tolerated.
5.2 Questionnaire data analysis A. Reliability test The most commonly used reliability measure is Cronbach’s Alpha (IBM, 2011; Coaks et al, 2008). A Cronbach’s Alpha higher than 0.7 is considered excellent (Coaks et al, 2008). The results obtained from the test are summarized in table (3) indicating excellent reliability. Table (3): Reliability Test results Variable Information provision Information collection User Interface Multimedia Emoticons Privacy Security Influence groups
Cronbach's Alpha 0.741 0.721 0.727 0.750 0.771 0.770 0.780 0.827
B. Correlation Bakeman and Robinson (2005) define correlation as a test to determine the possibility of the existence of a cause and effect relationship between the independent and the dependent variable.. To interpret the correlation results we need to look at the value of Pearson’s coefficient and its significance (Coaks et al, 2008). For the results to be significance, the value (p) should be less than 0.05 (Bakeman and Robinson; 2005).Table (4) presents the correlation matrix.
Provision
1
Collection
0.448
1
Interface
0.606
0.523
Multimedia
0.325
0.268 0.328
1
Emoticons
0.508
0.416 0.539
0.388
1
Privacy
0.419
0.332 0.526
0.343
0.538
1
Security
0.542
0.331 0.580
0.314
0.511
0.781
Influence groups
0.469
0.468 0.506
0.251
0.489
0.456 0.439
1
Inclusion
0.531
0.535 0.529
0.241
0.577
0.517 0.502
0.544
Inclusion
Influence Groups
Security
Privacy
Emoticons
Multimedia
Interface
Collection
Provision
Table (4): Correlation Matrix
1
1
1
Stepwise Regression Stepwise regression was conducted to develop a regression model that only includes the independent variables that statistically influence citizen inclusion in e- rulemaking (Bakeman and Robinson; 2005). Almost 42% (R square=0.418, P=0.000) of the changes in citizens’ inclusion in e-rulemaking are explained by the variables; interface, privacy, information collection, emoticons, and security. The model has a significance value of 0.000 indicating that it is statistically significant. The results are presented in table (6). It is important to note that research in the field of the use of social networks in political activism reaches similar R square results as reported by Oehri and Teufel, (2012); Burke et al, (2011); Nasir, (2010); Schlosberg et al, (2007) Ranerup, (2000). Table (5): Summary of hypotheses accepted or rejected Hypothesis
Significance
R squared
Accepted/Rejected
H1
p=0.625
0.196
Rejected
H2
p=0.000
0.190
Accepted
H3
p=0.000
0.280
Accepted
H4
p=0.615
0.058
Rejected
H5
p=0.000
0.227
Accepted
H6
p=0.000
0.268
Accepted
H7
p=0.490
0.252
Rejected
H8
p=0.157
0.197
Accepted
H9
p=0.00
0.418
Accepted
6. Discussion E-rulemaking deliberation variables affecting e-Rulemaking Information collection significantly affects citizen inclusion in e-rulemaking (t=0.190, p0.025). The government representatives communicated that although they are not obliged to change the drafted rules, the government should be keen on feedback collection and incorporation in the laws they draft (Beierle, 2003; Coglianese, 2006; Emery and Emery, 2005). The government representatives reported that they can provide citizens with as much information as they want but the rulemaking participation level would not increase if the feedback received from the citizens was not included in actual law making. On the other hand, 76% of the participants indicated that the quality of their feedback would improve if they were assured that attention would be paid to it, which further emphasizes the importance of feedback collection and analysis. But if there are no rules that require the government to incorporate the received feedback in the drafting of rules as there are laws that require them to publish information online, then the government should make it clear that they are not obliged to change the drafted rules according to the received feedback (Schlosberg et al, 2008; Shulman, 2005) so as not to raise citizens’ expectations SNSs’ technological variables affecting e-Rulemaking The user interface has the strongest correlation with citizens inclusion (t=0.280, p < 0.05). An erulemaking tool should have an easy to use interface (Nasir, 2010; Yetim, 2009). Fortunately the user interfaces of SNSs are usually uncomplicated as SNSs are generally characterized with ease of use (Asur and Huberman, 2010). The participants who filled the questionnaires confirmed these beliefs as most of them evaluated the interface of the prototype as easy to use (78%). More than 90% of them indicated that they are willing to use the prototype in e-rulemaking with its current design. The government representatives are not enthusiastic about increasing the costs of data collection and analysis if these costs do not reflect on increased levels of citizens’ inclusion. These costs could be justified as it appears that online text communications seem to be lacking in emotional and non-verbal expressions (Schlosberg et al, 2008; Min, 2007). 80% of the participants expressed that they use emoticons in their communications, and 89% of the participants perceived Emoticons as helpful in expressing their opinions, However, a relatively smaller number (77%) reported that they found multimedia helpful in communication. in the context of e-rulemaking; Communications though Emoticons has a significant effect on citizen inclusion (t=0.227, p0.015). It appears that the use of Emoticons would have a positive influence on citizens’ inclusion in e-rulemaking. The government should investment in developing mechanisms for the collection and analysis of such content. The third technological variable; Privacy, has a statistically significant effect on citizen inclusion in erulemaking (t = 0.268, p < 0.05). The interviewed representatives as well as many researchers believe that for an SNS to be used in e-rulemaking, it should have strong privacy options and should give the users control over their privacy settings (Wilson et al, 2009; Barnes, 2006; boyd and Heer, 2006; Gross and Acquisti, 2005). On the other hand, the representatives also believed it important to make citizens reveal some personal information about themselves, so as to ensure the quality of the discussions and the feedback the government receives. The privacy options of most social networks require a set of basic information to be publicly revealed to everyone, this includes; the user’s name, age, gender, marital status, and the regional area the user belongs to (Wilson et al, 2009). These information would satisfy the government’s need for revealing some basic information about the citizens without violating the citizens” sense of privacy.
Environmental variables affecting e-rulemaking Security has a statistically significant effect on citizen inclusion (t=0.252, p>0.05). Threats will always exist in the digital age (Kuzma, 2011; Oehri and Teufel, 2012) and it also has an effect on the outcomes we hope to achieve from the use of SNSs in e-rulemaking. In addition, the government has little influence over the security of the SNS it chooses to use, as it is physically outside of its reach which makes it harder to ensure the security of the SNS. Thus it is essential for a government engaging in e-rulemaking on SNSs to select an SNS with high levels of security to ensure the protection of the rulemaking process. Reaching a 100% secure social network is impossible and is not cost effective thus governmental agencies should choose an attainable security level and accept a certain degree of insecurity (Oehri and Teufel, 2012). Influence groups have a statistically insignificant effect on citizen inclusion in e-rulemaking (t=0.021, p>0.05). Both the interviewed representatives and researchers believe that some influence groups have a good online presence with better online mobilization than others, posing the threat that a government engaging in e-rulemaking would receive a large volume of comments that only reflect the interests of a single group unrepresentative of the Egyptian society (Shulman, 2009; Schlosberg et al, 2008; Emery and Emery, 2005; Coglianese, 2004), however, the representatives emphasized that the number of comments they receive does not matter, what matters is the value the comments would or would not add to the rulemaking process (Emery and Emery, 2005) The presence of interest groups on the SNS to be used in e-rulemaking would not increase citizen inclusion in rulemaking, as on an individual level this would not add much to the inclusion of individuals specially those not belonging to a certain influence group. This explains why the variable has an insignificant effect on citizen inclusion, and only a little over half of the respondents (55%) believed that influence groups have an effect on their political opinion How to use social networks in e-rulemaking? We believed that the proper use of SNS would increase citizens‟ inclusion in e-rulemaking. The American rulemaking process could be adopted to facilitate e-rulemaking through SNSs. Five of variables included in the study (information collection, user interface, communications in emoticons, privacy and security) have a significant effect on citizens’ inclusion in e-rulemaking at different stages of the e-rulemaking process. A government wishing to use SNSs in e-rulemaking should examine the contributed conceptual model contributed when examining the features of an SNS for e-rulemaking.
When a rule proposal is published online, the interface of the SNS, its privacy and available communications methods would affect the extent to which the citizens would provide their feedback to the government through it or not. The extent to which the government is keen on collecting the feedback of the citizens and incorporate it into rulemaking, would also affect their participation at this stage. The interface of the SNS and its privacy would affect citizen inclusion in the last stage of erulemaking. In this stage the government publishes the finalized rules online for the citizens to read them. Security would affect the use of the SNS in all the rulemaking process as it is an environmental threat always present whenever online communication are conducted
Figure (5): Contributed conceptual model
7. Conclusion This research examined the use of social networking sites in e-rulemaking. It examined variable extracted from the literature that are thought to affect e-rulemaking on SNSs and out of these variables it determined five of them that have a statistically significant effect on e-rulemaking on SNSs. This research contributes a conceptual and a research model that can be used by governments to conduct e-rulemaking over social networks. The research also illustrates how to use SNSs in e-rulemaking. The conceptual model can be expended in the future to include other variables affecting e-rulemaking other than those studied. The model could be adapted to the e-rulemaking process of different countries with minor modifications to fit the cultures of these countries. Based on the contributed conceptual model, questionnaires and interview results; a checklist has been developed that can be used to evaluate wither a government can use a certain networks in erulemaking or not which could make the transition to the use of SNSs smoother.
8. Limitations and future directions The participants of the study are considered a small sample. The study chose to focus on SNSs’ users only. The opinion of parliament representatives’ was not assessed in the study as it was dissolved in Egypt during the time at which this research was conducted. Future researchers are recommended to include these groups in their studies or to adopt a more statistically centered research methodology such as Structured Equation Modeling (SEM).
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