This paper analyzes anonymous political participation in the form of e-petition signing. The purpose of this study is to increase knowledge about patterns behind anonymous e-petition signing. Since online political participation evokes an important discussion about the balance between the need for transparency on the one hand, and the right for anonymity on the other hand, it is crucial to increase our knowledge of the factors affecting citizens’ choices to remain anonymous. Using quantitative content analysis of 220 informal e-petitions on the site adressit.com in Finland, this study seeks to find possible determinants for the share of anonymous signatures. Findings indicate that the type of demand presented in the e-petition is a key factor predicting the share of anonymous signatures.
Petition signing and anonymity
Data and methods
Discussion and conclusion
Democracy has an ambiguous relationship with anonymity. In the most basic act of political participation, voting, our political preferences are protected by the secret ballot. In other acts of political participation, e.g., large campaign donations, the norm is transparency. Ideally, there would not be a need for political anonymity to allow us to freely express ideas without fear of attack or ridicule, but we do not live in a perfect world . By studying when people choose to withhold their signatures from public scrutiny, we can gain understanding about the political behavior of citizens and the factors affecting the choice to participate in politics anonymously. This, in turn, can increase understanding of the role of anonymity in democracy, i.e., when, how and why it is used by citizens.
This article is examines the decision to withhold one’s name from public scrutiny when signing an online petition. While traditional forms of political participation are declining in numbers, new forms of political participation, driven by digital and social media, have emerged (Anduiza, et al., 2012). In particular, petition signing is becoming increasingly popular (Dalton, 2008; Riehm, et al., 2011). Starting, collecting signatures, and signing petitions is easier than ever before online. E-petitions seem to bring some hope to dystopian views due to decreasing levels of traditional political participation in Western democracies (Chadwick, 2012).
For the purpose of this paper, a petition is defined as a formal request to a higher authority, e.g., parliament or other authority, signed by one or a number of citizens (Macintosh, et al., 2002). Some regard online petitions as a new form of democratic innovation that could revive democracy, help measure public opinion, help citizens put issues on the political agenda (Jungherr and Jürgens, 2010) or serve as an entry point for greater political participation (Chadwick, 2012; Cruickshank, et al., 2010; Escher, 2011; Whyte, et al., 2005). Skeptics point to the reduced effort and cost of signing a petition online and thus classify online petitions as “meaningless” slacktivism (Breuer and Farooq, 2012; Christensen, 2011), concluding that their “transformative potential is very moderate” (Lindner and Riehm, 2009). Critics might therefore argue that anonymous e-petition signing is the ultimate form of slacktivism because it both requires just minimal effort and personal commitment. However, anonymity encourages e-petition signing by removing fear of harassment based on personal political opinions. La Raja’s (2011) findings indicate people are less likely to sign a petition if their signature will be made public on the Internet.
Green (2013) argues there is a need to study the link between privacy and petitioning online: “in a world without political obscurity , repercussions loom indefinitely. What is the real cost of signing petitions when doing so potentially creates a permanent record of one’s political beliefs in the everlasting memory of the Internet?”  Like other forms of political participation, petition signing online is linked with political anonymity. In some online petition platforms, signatures are listed in connection with the petition and thus made instantly public. Allowing e-petition signers to withhold their name from publication is a Web site design decision; the design may force signers to publish their name online (Hale, et al., 2013). In other cases, e-petition signers may choose not to reveal their name, perhaps because of the possible social consequences of supporting a political issue.
The purpose of this study is to increase knowledge about patterns behind anonymous e-petition signing. The aim of the study is investigate the link between e-petitions characteristics and signature disclosure by citizens in a representative democracy; which e-petitions characteristics have an effect on the share of anonymous signatures?
Online petitions can be either formal or informal (Lindner and Riehm, 2009). Petitions where citizens see a clear relationship between their participation and its outcome are more likely to lead to community empowerment (Pratchett, et al., 2009). It seems illogical to sign a petition if one does not believe it to have some impact on reaching its goals. However, signing an petition may not require too much effort by the citizen and thus does not “cost” as much as other forms of political participation, like voting or taking part in a demonstration. When political participation is reduced to providing a name and an e-mail address online, it raises questions of what effects the lowered participation costs have on the political behavior of citizens. Online petitions have a somewhat indistinct role in representative democracy as there is an ongoing debate of their effectiveness. Critics argue online petitions might lead to decreased legitimacy of democracy as the petition process often fails to reach its goals (Chadwick, 2012; Peixoto, 2013). Proponents, conversely, see online petitions as a complimentary form of participation that can help increase citizen satisfaction with democracy (Frilander and Sannikka, 2012).
Online petitions have been studied from different perspectives: successfulness/effectiveness (Cotton, 2012; Hale, et al., 2013: Wright, 2012), growth rate (Hale, et al., 2013), institutional modernization (Lindner and Riehm, 2009), cohort trends in petition signing (Caren, et al., 2011), the socio-demographics of petitioners (Lindner and Riehm, 2011), likelihood of donating money (Lee and Hsieh, 2013), anonymous dissent (Riley, 2009), connection between social media support and actual signatures (Panagiotopoulos, et al., 2011), youth culture petitioning (Earl and Schussman, 2008), privacy preservation (Diaz, et al., 2009), the introduction of the national citizens’ initiatives (Emtö, 2013), and the reasons behind petition signing (Alexander, 2009).
Signing an online petition is the most popular form of online political activity in several countries (Chadwick, 2012; Hoffman, et al., 2013; Mahendran and Cook, 2007). Most online petitions, however, fail to reach their goals and gather enough signatures to have an impact (Hale, et al., 2013; Yasseri, et al., 2013). Online petitions seem to be dependent on mass media coverage for success, thus showing the importance of actively garnering media coverage when initiating a petition (Wright, 2012). Basically, a petition’s fate is set within the first 24 hours of its introduction (Yasseri, et al., 2013). The provision of social information matters; people are more likely to sign an online petition if they know many others have done so, suggesting there is a critical mass for the success of a petition (Margetts, et al., 2009). Lindner and Riehm (2011) found that e-petitions seemed to “predominately attract highly mobilised and politically active individuals with a disproportionately high socio-economic status.”  Yet, scholars have not investigated the connection between e-petition characteristics and the share of anonymous signatures. Since this is unexplored territory and petitioning can be regarded as a form of political communication, I depart from Lasswell’s (1948) model of communication as a guideline for characterizing e-petitions. E-petitions will be, within this study, characterized according to who says what to whom (in which channel) with what effect. In this case, the channel will be e-petitioning and the effect will be the share of anonymous signatures. Additionally, I investigate how the message in the e-petitions is presented.
Petition signing and anonymity
“But signing a petition today brings consequences beyond public criticism. The real threat of disclosure for modern petition signers is not tangible harassment, but the loss of ‘political obscurity’ in a modern data architecture that exposes citizens to indelible Internet scrutiny and rampant political preference cataloguing.” 
Research by La Raja (2011) has shown that signature disclosure online discourages people from signing petitions. Due to voting secrecy, citizens can make a choice not to reveal their party choice. They cannot always make the same choice when signing an online petition. The ability to hide signers’ names from public scrutiny is a choice made by the designer of the petition site. The Internet makes spreading information about political activity easy, which means citizens should not automatically assume their actions are private. 
Disclosure of one’s political preferences — as in signing an online petition — might create concern about disagreement and discomfort in relations among friends, colleagues and neighbors . Expressing political opinions may threaten social ties, which, in turn, gives the citizen a reason to withhold his/her opinions. Giving citizens an option to hide their signatures from online publication might therefore increase participation but at the same time, as Riley (2009) argues, decrease the legitimacy of the e-petition. Boudin (2011) argues petitions such as ballot initiatives always “should be subject to public scrutiny and disclosure” since these kinds of petitions ought to be considered as lawmaking, rather than petitions or political speech. However, all petitions are not formal enough to be considered lawmaking. Informal petitions, without an institutional link, might be closer to mere opinion expression, and thus resemble political speech more than lawmaking.
Is the social cost of signing a petition the same for all types of issues? La Raja (2011) states that the cost of supporting highly controversial issues may subject the petition signer to personal harassment from the opposition. The founding fathers of America seemed to be aware of this, given that a large part of political speech on controversial issues remained unsigned or was signed with a pen name during their time . Some issues are probably more likely to result in social cost than others. If an issue is likely to result in social costs, it is rational to avoid disclosing one’s preferences. Reasons to prefer anonymity include: fear of repercussions, isolation, or losing one’s job due to political opinions. For example, signing a petition in favor of the legalization of marijuana might have different consequences for an individual than signing a petition for lowering gas taxes.
Peddinti, et al. (2014) found that content sensitivity had an impact on Twitter users’ degree of anonymity. Twitter accounts dealing with sensitive issues like pornography, marijuana, islamophobia and homosexuality had 21 percent anonymous followers. Twitter accounts coded as dealing with non-sensitive issues (e.g., movies, family recreation, news) had at most nine percent anonymous followers . The more sensitive/controversial issue the Twitter account dealt with, the larger share of anonymous followers it attracted.
Similar to paper based petitions; electronic petition systems may produce unreliable results in the form of duplicate signatures. Some systems gather personal information from the signers to prevent this. However, this is not necessarily a privacy-friendly method when political opinions are expressed, as databases might be hacked. Therefore, privacy-preserving e-petition systems, just as e-voting systems, are needed to preserve citizens’ anonymity without the possibility of multiple signatures from one person (Verslype, et al., 2008; Diaz, et al., 2009). Green  argues the real threat of disclosure is loss of political obscurity, which exposes citizens to “indelible Internet scrutiny and rampant political preference cataloguing.” This can be exemplified using a case in the U.S., where gay rights opponents were upset once a court made it clear that the names of the signers of a petition (supporting a referendum to overturn support for gay and lesbian rights) would be disclosed on the Internet .
An international comparison reveals that some petition sites publish the full name of the signers, others replace the full name with initials, while some do not publish names at all (Bershadskaya, et al., 2013). Riehm, et al. (2011) concluded that publication of signers’ names on the Internet did not seem to be an absolute necessity in the German Bundestag e-petition system, since signature lists for mass and group petitions were not accessible to the public. In 2012, the possibility for pseudonymous signing was introduced in the German Bundestag e-petition platform. Users were thus able to have a pseudonym listed instead of their real name on the publicly available list of supporters. After the design change, a small but not statistically significant increase in signatures was noted (Schmidt and Johnsen, 2014). A majority of signers, some 76 percent, preferred to use a pseudonym, but this was regarded as a “default effect” by the authors, since the default setting was pseudonymous signing. ”Thus, the fairly high proportion of pseudonymous signatures would not be an indication for the users’ discomfort towards linking their name to a political issue, but rather evidence for a notable structuring effect of software design.” 
In a survey of German Bundestag e-petition platform users (n=215), Schmidt and Johnsen  found that almost half of the users stated that they sign e-petitions with their real names in either most cases or always. About 40 percent of the users opted to sign pseudonymously always or in most cases. Consequently, the users seem divided into two almost equal camps when it comes to how they think about pseudonymous e-petition signing. Twenty-seven percent revealed always signing under a pseudonym, whilst 32 percent stated they always signed with their real name, which indicates that about 59 percent of the users had already made up their mind about how they are going to sign any e-petition. Eleven percent of users claimed they sometimes sign under a pseudonym and sometimes by real name. Thus, it seems plausible that a majority of e-petition signers are not affected by e-petition characteristics when making up their mind about signing an e-petition pseudonymously or not. By implication, this suggests there are some e-petition characteristics which might influence whether or not citizens sign e-petitions anonymously.
Which properties of e-petitions affect the share of anonymous signatures? The dearth of research regarding political anonymity makes it difficult to answer this question. Therefore, an explorative approach has been employed to identify possible determinants for the share of anonymous signatures, by coding e-petitions for variables used in previous research (e.g., Cotton, 2012; Lindner and Riehm, 2011; Schmidt and Johnsen, 2014). Using Lasswell’s (1948) classic model for political communication, these determinants were adapted and sorted according to who (initiator gender, initiator anonymity, initiator type) says what (topic, controversiality, demand type, level) to whom (addressee), how (signal/tone, preparation, argumentation, affectivity, future, traditional media, social media, Web link) and with what effect (share of anonymous signatures). Additionally, form aspects as when (creation year) the e-petitions were created, and the length of the petition texts, have been covered.
Data and methods
The empirical data used in this study originated from the Finnish e-petition site www.adressit.com. This site is an informal e-petition “warehouse” site (cf., Van Laer and Van Aelst, 2009) established in 2006 by a private entrepreneur, Mr. Samppa Rehu, who administers the site and provided access to the data. Visitors can create, view or sign petitions online. The information required about the creator of an online petition is a functioning e-mail address. Creators of a petition have the option of withholding their real name. Signers are asked to enter their full name, address and home country. Submitting an e-mail address and revealing one’s name online is optional for signers. This results in a unique opportunity to study when citizens chose to make their political participation public online. More specifically, it can tell us when they prefer not to.
Adressit.com is the largest informal e-petition Web site in Finland and contains over 5,000 petitions . Adressit.com makes an interesting case study because it has existed for a relatively long time and can be considered as rather well-established even though it is facing competition from the formal e-petition sites kuntalaisaloite.fi and kansalaisaloite.fi. In the media, the site has received criticism for being ineffective (Mikkola, 2007), being susceptible for fraud (Viitasaari, 2012)  and hosting discussions of low quality (Marjamäki, 2012). Nevertheless, the site contains e-petitions which vary greatly in characteristics, which means the potential impact of these characteristics on the share of anonymous signatures can be examined.
There are several reasons behind the decision to study a Finnish site. Firstly, Finland has one of the highest rates of regular Internet use in the EU (91 percent) and a high (92 percent) Internet penetration making it suitable for inquiry about e-petitions (https://ec.europa.eu/digital-agenda/en/scoreboard/finland). Secondly, petition signing (off-line and online) is among the most popular types of political participation among Finnish citizens. About one half of the Finnish electorate has signed some kind of petition . Thirdly, the introduction of the formal petition system (see kansalaisaloite.fi) in 2012 makes Finland the first Nordic country to institutionalize citizens’ initiatives online on a national, state level (Emtö, 2013). In other words, e-petitions seem to have an established societal role in Finland.
The data file included the share of anonymous signatures and URLs for 4,392 e-petitions on adressit.com. Due to economic reasons, a randomized sample of 219 e-petitions (five percent) was chosen for analysis. I used quantitative content analysis to examine the characteristics of the e-petitions; the unit of analysis is consequently an e-petition. Each e-petition was coded for 18 independent variables of interest. In addition to basic characteristics as form, the variables covered who says what to whom, how and with what effect (cf., Lasswell, 1948) using the e-petitions as a means of political communication and participation. The dependent variable of interest was the share of anonymous signatures. The e-petitions were coded during five weeks in September–October 2014. Intercoder reliability of the coding scheme was calculated using percent agreement and Krippendorff’s alpha (Krippendorff, 2004). Overall, inter-agreement was 89 percent, and Krippendorff’s alpha exceeded the threshold of 0.8 (Krippendorff, 2004), ranging from 0.68 to 1.00. In general, reliability was moderate to high for most variables (according to Krippendorff (2004) an alpha value over 0.67 is sufficient for tentative conclusions).
The first step in the analysis was to find out which of the independent variables had a statistically significant effect on the dependent variable, i.e., the share of anonymous signatures. Since almost every independent variable was measured on a nominal or ordinal scale and the share of anonymous signatures was non-normally distributed according to the Kolmogorov-Smirnov test, Kruskal-Wallis H-tests and Mann-Whitney U-test were performed to single out statistically significant independent variables. These independent variables were then entered into a general linear model regression analysis to determine whether the statistically significant differences between categories in the bivariate analyses remained when controlling for other variables. A general linear model is not particularly sensitive to outliers and thus robust to non-normal distributions (SPSS, 2009).
Table 1: Descriptive statistics about e-petitions.
Notes: *Missing cases due to deletion of petition info on adressit.com during coding process.
**Measured in number of characters including blank spaces.
Median Minimum Maximum N Share of anonymous signatures 32.2% (0.15) 29.7 3% 97% 219 Signatures 1,085 (2,445) 327 102 29,092 219 Signatures per IP 1.28 (0.63) 1.16 1 9.27 219 Comments 27.3 (74.1) 5 0 576 216* Comments per signature 0.04 (0.16) 0.01 0 1.81 216* Length of text** 1,659 (1,791) 1,174 6 21,316 216* Active 71 % — — — 219 Age in days 1,505 (737) 1,554 21 2,633 219
Judging from the general descriptive statistics shown in Table 1, the share of anonymous signatures, the dependent variable, varied greatly between e-petitions. In total, about one third of the online signatures on adressit.com were done anonymously. The mean number of signatures per e-petition is 1,085, but the standard deviation was high. On the one hand, the number of signatures per IP address can be a coarse measure of misuse or faking of signatures. On the other hand, different family members might sign an e-petition using the same computer, and therefore use the same IP address. In general, the mean number of signatures per IP address was rather low (1.3). When comparing the mean number of comments per signature, the ratio was low (0.04). In relation to the number of signers, few people chose to comment on an e-petition. The standard deviation regarding the mean length of the e-petition texts indicated a rather high degree of variation. A majority of the e-petitions (71 percent) were still active at the time of coding even though the earliest data originated from 2006.
Table 2: Share of anonymous signatures according to independent variables part 1/2.
Notes: Bivariate Kruskal-Wallis H-test and Mann-Whitney U-test were used to examine statistically significant differences between categories. *p<0.05, **p<0.01, ***p<0.001.
† Statistically significant correlation between independent and dependent variable detected using Spearman’s rank-order correlation coefficient, rs =-.448, p=.000.
†† Statistically significant correlation between independent and dependent variable detected using Spearman’s rank-order correlation coefficient, rs =-.301, p=.000.
Variable group Independent variable Categories Share of anonymous signatures, mean Standard deviation N Percentage Form Creation year† *** 2006 0.38 0.10 34 16 2007 0.38 0.15 36 16 2008 0.38 0.21 32 15 2009 0.31 0.14 38 17 2010 0.29 0.09 26 12 2011 0.24 0.10 20 9 2012 0.22 0.09 26 12 2013 0.24 0.09 7 3 Length of text†† *** Who? Initiator gender * Unable to tell 0.37 0.16 41 19 Woman or majority of women 0.30 0.26 97 45 Man or majority of men 0.32 0.31 78 36 Initiator anonymous ** No 0.30 0.13 168 78 Yes 0.39 0.18 48 22 Initiator type *** Organization/group 0.23 0.08 39 18 Individual 0.33 0.14 146 63 Anonymous 0.39 0.16 31 19 What? Topic *** Education, science & technology 0.25 0.11 39 18 Employment, national economy, taxes 0.31 0.11 17 8 Environment, transport & traffic 0.26 0.10 43 20 Media, culture, entertainment 0.43 0.19 36 17 Social issues, health care 0.29 0.12 27 13 Religion, moral & ethics, drugs & alcohol 0.31 0.09 13 6 EU, international issues 0.39 0.15 11 5 Other 0.38 0.15 27 13 Controversial topic No 0.32 0.15 203 95 Yes 0.34 0.11 10 5 Demand type *** Specific, pro establishment, preservation 0.24 0.11 83 39 Specific, con establishment, shutdown, resignation, boycott 0.31 0.11 42 20 Specific, demand about law change 0.34 0.09 34 16 General demand 0.33 0.11 20 9 Other 0.50 0.16 34 16 Level *** National, international 0.38 0.13 112 53 Municipal, regional 0.26 0.13 101 47
Moving on to the possible determinants for the share of anonymous signatures, Table 2 shows who petitioned about what. Table 3 concerns to whom the e-petitions were directed, and how they were presented. The two tables are split due to length reasons. Out of the nine independent variables examined in Table 2, only one — controversial topic — did not have a statistically significant effect on the share of anonymous signatures. There were few (n=10) e-petitions concerning controversial topics in the analyzed sample . However, since this is a surprising finding, I conducted an additional test to check if this finding was due to the low number of controversial topics in the sample. A stratified sample of an additional 30 e-petitions coded as controversial topics was added to the randomized sample. Nevertheless, a bivariate Mann-Whitney U-test showed no statistically significant difference (p=.111) between the share of anonymous signatures when comparing controversial (n=40, M=0.34, SD=0.13) and non-controversial (n=203, M=0.32, SD=0.15) e-petition topics. Furthermore, six variables (creation year, length of text, initiator type, topic, demand type and level) had a statistically significant effect at the significance level of p<0.001. The creation year of the e-petition correlated with the share of anonymous signatures: since 2009, the share has been decreasing. The length of the e-petition text correlated negatively with the dependent variable, indicating that longer texts tended to have a lower share of anonymous signatures. The gender of the initiator did not have an impact on the share of anonymous signatures, even though there is a statistically significant difference which is caused by the category “unable to tell”. The difference between men and women is relatively small, 0.02, and not statistically significant. Petitions with anonymous initiators were more likely to attract a higher share of anonymous signatures as indicated by the nine percent difference depending on initiator anonymity.
There were indications of an effect showing that e-petitions initiated by organizations or groups tended to have a lower share of anonymous signatures compared to e-petitions initiated by individuals, while anonymous initiators had the highest share among the categories. Concerning e-petition topics, “softer” issues touching upon media, culture and entertainment as well as EU-related, international issues seemed to attract a higher share of anonymous signatures than the other categories. Demand types that were specific and in favor of an establishment or wanted to preserve something was the largest category for the variable demand type and had the lowest share of anonymous signatures. The more unspecific demand type category, “other”, had a high share (50 percent) of anonymous signatures. More locally and regionally oriented issues had a lower share of anonymous signatures compared to issues on a national/international level, as illustrated by the variable “level” in Table 2.
Table 3: Share of anonymous signatures according to independent variables part 2/2.
Notes: Bivariate Kruskal-Wallis H-test and Mann-Whitney U-test were used to examine statistically significant differences between categories. *p<0.05, **p<0.01, ***p<0.001.
Variable group Variable Categories Share of anonymous signatures, mean Standard deviation N Percentage To whom? Addressee *** Public authority (e.g., Parliament, government) 0.33 0.11 70 33 Municipal decision-maker or institution 0.23 0.08 77 36 Private company or organization 0.41 0.19 42 20 The public 0.30 0.17 7 3 Other/don’t know 0.47 0.09 17 8 How? Signal/tone *** Positive 0.21 0.05 30 14 Neutral 0.35 0.16 130 61 Negative 0.31 0.11 54 25 Preparation *** Very prepared 0.24 0.09 28 13 Prepared 0.30 0.13 130 61 Poorly prepared 0.40 0.16 56 26 Argumentation ** Thorough argumentation 0.21 0.08 8 4 Argumentation 0.31 0.14 176 82 No argumentation 0.39 0.17 30 14 Affectivity * Not emotional 0.31 0.14 164 77 Emotional 0.36 0.16 49 23 Future No 0.32 0.15 131 66 Yes 0.33 0.14 68 34 Traditional media No 0.33 0.15 179 90 Yes 0.29 0.11 20 10 Social media No 0.32 0.15 192 97 Yes 0.39 0.19 7 3 Web link No 0.32 0.15 147 74 Yes 0.33 0.14 52 26
Statistically significant effects were found for five of the nine independent variables shown in Table 3. The e-petitions addressed both public and private actors and the share of anonymous signatures was higher for private companies and organization compared to public actors. The cases where the addressee was unknown or difficult to determine resulted in a higher share of anonymous signatures. The signal or tone of the headline of an e-petition had a statistically significant impact on the dependent variable suggesting a positive tone resulted in a lower share of anonymous signatures. Concerning preparation quality, there was a negative linear effect: better prepared e-petition texts resulted in a lower share of anonymous signatures. A similar effect was detected for the variable argumentation, which showed, in particular, that e-petition texts lacking argumentation tended to acquire a higher share of anonymous signatures. However, it is worth noting that the number of e-petitions featuring “thorough argumentation” was low (n=8). E-petition texts where emotions were clearly evident had a statistically significant higher share of anonymous signatures.
Next, to determine the independent influence of each independent variable on the share of anonymous signatures, the variables for which statistically significant independent effects were found in the bivariate analyses were entered as predictors in a univariate general linear model (Table 4).
Table 4: Univariate general linear model analysis. Part 1/2.
Notes: ^p<0.10, *p<0.05, **p<0.01, ***p<0.001. a Last category was used as reference category for the independent variables. Only statistically significant independent variables from bivariate tests (see Tables 2 and 3) were used in this regression model. A regression analysis model featuring all variables was also performed. This model resulted in a slight increase in the adjusted R2 value (0.044), but none of the omitted variables had a statistically significant effect on the dependent variable.
Variable group Independent variable Categories Beta coefficient S.E. Partial eta squared N Percentage Form Creation year -,011* ,000 ,034 Length of text ,000 ,000 ,001 Who? Initiator gender Unable to tell -,043 ,042 ,006 41 19 Woman or majority of women -,021 ,017 ,008 97 45 Man or majority of men 0a 78 36 Initiator anonymous No -,107* ,052 ,023 168 78 Yes 0a 48 22 Initiator type Organization/group ,008 ,047 ,000 39 18 Individual ,059 ,049 ,008 146 63 Anonymous 0a 31 19 What? Topic Education, science & technology ,018 ,032 ,002 39 18 Employment, national economy, taxes -,014 ,036 ,001 17 8 Environment, transport & traffic ,018 ,031 ,002 43 20 Media, culture, entertainment ,051^ ,028 ,017 36 17 Social issues, health care ,041 ,033 ,008 27 13 Religion, moral & ethics, drugs & alcohol -,021 ,040 ,001 13 6 EU, international issues ,071^ ,043 ,015 11 5 Other 0a 27 13 Level National, international ,016 ,029 ,002 112 53 Municipal, regional 0a 101 47 R2=.566; Adjusted R2=.494; N=219
Four of 15 independent variables had a statistically significant effect on the share of anonymous signatures (adjusted R2=.494). Three of these are shown in Table 4 and one in Table 5 due to length reasons. The effects of creation year, initiator anonymity and demand type remained statistically significant when controlling for other variables. The e-petitions had a decreasing share of anonymous signatures for every year, although it is evident in Table 2 that the decrease did not start before 2009, after remaining stable for the years 2006–2008. Anonymous initiators predicted the share of anonymous signatures; people were more likely to follow the example of an anonymous initiator and remain anonymous themselves. The effect of demand type suggests the “other” category, which was used as a reference category in Table 4, seemed to have a great influence on the dependent variable.
Table 5: Univariate general linear model analysis. Part 2/2.
Notes: ^p<0.10, *p<0.05, **p<0.01, ***p<0.001. a Last category was used as reference category for the independent variables.
Variable group Variable Categories Beta coefficient S.E. Partial eta squared N Percentage To whom? Addressee Public authority (e.g., Parliament, government) -,011 ,038 ,000 70 33 Municipal decision-maker or institution -,036 ,044 ,004 77 36 Private company or organization ,022 ,034 ,002 42 20 The public -,063 ,054 ,007 7 3 Other/don’t know 0a 17 8 How? Signal/tone Positive -,025 ,028 ,004 30 14 Neutral ,022 ,021 ,006 130 61 Negative 0a 54 25 Preparation Very prepared -,071* ,032 ,026 28 13 Prepared -,049* ,020 ,033 130 61 Poorly prepared 0a 56 26 Argumentation Thorough argumentation ,027 ,054 ,001 8 4 Argumentation ,024 ,025 ,005 176 82 No argumentation 0a 30 14 Affectivity Not emotional -,014 ,018 ,003 164 77 Emotional 0a 49 23 R2=.566; Adjusted R2=.494; N=219
The last independent variable which had a statistically significant effect in the regression analysis (Table 5) was preparation quality. The beta coefficients showed that the share of anonymous signatures was lower the better prepared an e-petition was. The other variables, concerning to whom the e-petition was directed, and how the e-petition was put forward, did not result in statistically significant effects.
As indicated by the partial eta squared values in Tables 4 and 5, the independent variables explaining most of the variance in the share of anonymous signatures were (from largest to smallest): demand type, preparation quality, year of creation, and initiator anonymity (see Figure 1). A general linear model regression analysis including only these four independent variables resulted in an adjusted R2 value of .460, a mere .034 lower than the model presented in Tables 4 and 5.
Figure 1: The determinants of the share of anonymous signatures.
Discussion and conclusion
The purpose of this study was to increase knowledge about patterns behind anonymous e-petition signing. Using quantitative content analysis, it investigated the link between e-petitions characteristics and signature disclosure on an informal e-petition platform in Finland. The study sought to address: which e-petitions characteristics have an effect on the share of anonymous signatures?
Approximately a third selected the anonymous option when signing e-petitions at adressit.com, indicating that the option is valued amongst the users. This is much less than the 76 percent pseudonymous signatures Schmidt and Johnsen (2014) found at the German Bundestag e-petition platform. However, the numbers are not fully comparable because the default option on the German platform was pseudonymity. In contrast, the default option for signers at adressit.com is name disclosure. Nevertheless, a third of the signers at adressit.com actively choose to be anonymous. In general, when comparing these results with the German findings, a default choice effect seems to exist, with citizens sticking to the default option the e-petition platform provides.
Surprisingly, and contrary to previous research (cf., La Raja, 2011; Peddinti, et al., 2014), the controversiality of the e-petition topic did not have a statistically significant effect on the share of anonymous signatures. A possible explanation could be that citizens attracted to signing controversial e-petitions are already activists with both time and effort invested in the cause and might not be concerned by any risk in disclosing their preferences.
Several independent variables remained statistically significant predictors when entered into the general linear model, indicating that some of the variation in the share of anonymous signatures is due to e-petition characteristics. One of these predictors, the creation year of the e-petitions, showed a clear trend of a decreasing share of anonymous signatures since 2009. Arguably, the decreasing share of anonymous signatures might be a result of changing online norms, making real name policies more common and accepted among citizens. Facebook, constantly pushing a real name policy, started to gain ground in Finland in 2007 and was translated into Finnish in 2008 (Kauppi, 2008). By 2011, about half of the Finnish population used some kind of social media (Statistics Finland, 2011). Of course, this is speculative, the site adressit.com might have become more wide known and familiar to citizens, giving them incentives and making them more comfortable with the idea to sign e-petitions with their real name on adressit.com.
People were more likely to sign e-petitions anonymously if the e-petition initiator was anonymous. This suggests anonymity is contagious in the sense that citizens seem to follow the initiative of the initiator and remain anonymous themselves. Perhaps an uncertainty about the true motivations of the initiator gives rise to doubts in the mind of the signer regarding the seriousness of the e-petitions. This finding echoes previous research showing that people usually try to adapt to the behavior of others to fit in into the social norm .
The topic of the e-petition did have an effect on the share of anonymous signatures as the demand type turned out to be the most influential statistically significant predictor. Roughly put, the more specific and in favor of something an e-petition was, the smaller share of anonymous signatures it produced. E-petitions with vague demands tended to get a larger share of anonymous signatures. This finding suggests it is easier for citizens to use their real name when the demand of the e-petition is clearly specified and presented in a positive tone, compared to more diffuse demands presented in a negative tone. Moreover, vague demands can indicate less serious e-petition texts, which might explain the high share of anonymous signatures for the demand type “other” .
Higher quality e-petition texts produced a lower share of anonymous signatures, suggesting preparation quality is a key predictor. This finding points to the trend that people are less willing to sign less serious, poorly prepared e-petitions with their own name. Maybe people are more likely to sign better prepared e-petitions because they believe these will have a chance of causing change in contrast to less prepared e-petitions. Furthermore, people might support the cause of the petition, but are unwilling to become affiliated with it due to the low quality of the e-petition text and therefore sign anonymously. Better prepared e-petitions might be considered to have a better chance of reaching success and people might have a winner bias, i.e., an incentive to publicly support e-petitions they regard as probably successful. When e-petitions are more poorly prepared they take a chance and sign them anonymously; a more risk free behavior.
In conclusion, this study shows there are several e-petition characteristics affecting the share of anonymous signatures. At a first glance, most of the possible predictors presented and tested in the study seemed to have an effect on people’s choice to sign e-petitions anonymously. However, most of these lost their statistical significance when controlled for in a general linear model. Nevertheless, four variables stood out as significant predictors and could explain quite a lot of the total variance in the share of anonymous signatures. Previous research on political anonymity has not investigated reasons behind citizens’ choice to act anonymously, thus revealing few hints about what could possibly impact such a decision. This study, however, has shown that the variance in the share of anonymous signatures can be attributed to specific e-petition characteristics as demand type.
This study has hopefully increased understanding of when citizens tend to act anonymously when signing e-petitions, which begs the question of why they do so. Future studies may help in understanding the reasons and motivations for acting anonymously, since this is an option citizens use when given the chance. By widening the scope from e-petitions, future research could deal with other forms of political participation such as political donations and online political discussion, where anonymity is an option for citizens.
About the author
Janne Berg is a Ph.D. student in the Department of Political Science at Åbo Akademi University in Finland.
E-mail: jaberg [at] abo [dot] fi
The coding scheme is available on request from the author.
1. Scott, 2004, p. 139.
2. Political obscurity refers to individual control over the scope of public knowledge about one’s political preferences (Green, 2013, p. 371).
3. Green, 2013, p. 382.
4. Lindner and Riehm, 2011, p. 1.
5. Green, 2013, p. 367.
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15. In a famous example of an online petition that was accused of gathering false signatures, most of the signatures could later be verified to be genuine; see Häyhtiö and Rinne, 2008, p. 314.
16. Borg, 2013, p. 54.
17. On a general level, issues that evoke strong emotions, exist on the border between the public and the private, and deal with individual freedom were coded as controversial issues. For example, petitions with headlines as “No to gay marriage”, “Stop vaccines against the swine flu” or “At least not a sixth nuclear power plant to Finland” [author’s translation from Finnish].
18. See Stromer-Galley and Martey, 2009, pp. 1,043–1,045.
19. This category included e-petitions that demanded, for example, an artist to come and perform to Finland, a change of board members for an ice hockey club, or a redesign of a Finnish social media platform. In other words, it contained demands that were less “political” or policy-related than the other categories.
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Received 18 January 2016; revised 22 September 2016; accepted 16 November 2016.
Copyright © 2017, Janne Berg. All rights reserved.
The dark side of e-petitions? Exploring anonymous signatures
by Janne Berg.