The Role of Framing on Male and Female Undergraduate Students’ Feminist Digital Activism

Edward Chan

According to Pew Research, almost 80% of American adults are active online and 75% get their news from email or social media updates (2011). With such a large population dependent on online resources to gain knowledge, form opinions, and take action, it is imperative that research examines the most effective methods to garner individual’s attention in order to invoke digital activism. Digital activism is defined as the use of the Internet or any Internet-based application to promote a political or social cause, generate awareness, and receive global support for social justice initiatives (Mitu, Vega, & Diego, 2014).

The rise of digital activism has led to extensive research on the ability to influence people’s involvement in various causes (Mitu, Vega, & Diego, 2014). Framing is one technique that has been extensively explored in terms of its influence on a person’s actions. The act of framing is the process in which an informative source presents a political or social matter in a way that constructs and defines the issue for the audience (Nelson, Zoe, & Rosalee, 1997). The way in which social and political causes are framed can come in a variety of constructs such as positive and negative framing. More specifically, positive framing is defined as a particular situation that highlights a possible gain, and negative framing is defined as a particular situation that highlights a possible loss (Por & Budesco, 2013). For example, positive framing is when lottery companies highlight potential financial gains and negative framing is when anti-smoking campaigns highlight potential health risks. Negative and positive framing are utilized every day through the medium of digital activism to promote social and political campaigns such as abortion, human rights, and feminism (Gang & Zhu, 2014).

In the early 1980s, framing effects were studied for the first time in the hopes of establishing an understanding of the effects of positive and negative framing on action-taking (Kahneman & Tcsky, 1984). Findings showed that when people were presented with positively-framed scenarios, they were less likely to take action than if they were presented with negatively-framed scenarios (Por & Budesco, 2013). Later studies confirmed Kahneman and Tcsky’s initial findings regarding framing and helped pave the way for analyzing influences brought upon by framing effects, which eventually led to the development of prospect theory (1984). Prospect theory states that a loss has a greater influence on action-taking than an equivalent gain does (Gang, 2014). For example, negative framing significantly increases intentions to perform health-related behaviors such as obtaining vaccination shots (Block, Luarne, & Punam, 1995).

Furthermore, current literature shows that women are significantly more reactive towards negative framing in general (Ellingsen, Johannason, Mollerstorm, & Munkhammar, 2013). Specifically, women have higher response rates towards negatively-framed information that presents a specific charitable goal than men (Huang & Wang, 2010). This is consistent with other studies that found women to be more altruistic than men and more likely to help their community (Eckel & Grossman, 1998; Fujimoto & Park, 2010). These findings suggest that women respond at higher rates to negative framing and altruistic initiatives like digital activism for various causes. Unfortunately, the extensive body of literature on the relation between framing and action-taking has yielded no empirical data regarding framing effects and feminist digital activism. This study will not only attempt to address a critical knowledge gap between framing and feminist digital activism, but it will also evaluate the variation across gender.

Research Questions

The current study seeks to investigate the following research questions: (1) What is the difference in outcomes of negative and positive framing on feminist digital activism? 2) What is the difference in outcomes of gender on feminist digital activism? 3) What is the interaction of gender and framing on feminist digital activism? Following these questions, the hypotheses of this study are: 1) Negative framing will elicit more responses towards pro-feministic digital activism 2) Females will be more likely to respond towards feminist digital activism. 3) Females will be more likely to participate in feminist digital activism if the message is framed negatively. In this study, feminist digital activism is operationalized as taking an initiative to learn more about feminism through an online source. Thus, the amount of people who were willing to open the email to learn more information about the cause, based on the framing of the subject line, demonstrated the rate of framing effects on digital activism.

Method

Participants and procedure. This study employs a randomized, between-groups design in order to analyze the effects of message framing and gender on digital activism. Participants’ emails were gathered by accessing the New York University Applied Psychology Undergraduate Gmail database. Of 409 total emails, nine were removed because the participant’s gender was not identifiable. Of the remaining 400 participants, 84 were men and 316 were women. Once a complete list of emails was established, participants were randomly separated in a systematic manner into two groups of 42 males and 158 females. These groups were assigned to receive either a positively-framed or a negatively-framed email. Due to errors with receiving the emails, 8 women from the negative campaign were removed from the study, and 8 men from the positive campaign were removed. In conclusion, there were 150 women in the negatively-framed campaign, 158 women in the positively-framed campaign, 34 men in the positively-framed campaign, and 42 men in the negatively-framed campaign.

The emails were composed in the name of a fake feminist organization called “Fight for Feminism Today”. The positively-framed email included encouraging words such as “celebrate” and “cherish” both in the subject line and within the email. Pictures representing equality, feminine strength, and equal wages were featured within the positively framed email as well. An example of equality and feminine strength in the positively-framed email is depicted by the 1943 “We Can Do It” picture that represents feminist ideals through their ability to function at the same degree as men in the workforce (Doyle, 2009). The negatively-framed email included a discouraging subject line, using phrases such as “failed” and “lacking support”. Pictures representing inequality, hopelessness, and cat-calling were featured within the negatively-framed email. An example of inequality and cat-calling in the negatively-framed email is depicted by a screen shot of the viral video, “10 Hours of Walking in NYC as a Woman,” in which men subjugate women to derogatory terms and phrases such as “hey baby” and “you should say thank you, I’m calling you beautiful” (Bliss, 2014).

The emails were sent out to participants through an analytic website called Mailchimp. Mailchimp recorded the participants’ rate of digital activism by analyzing the amount of people who opened the email. After allocating one week for participants to open the emails, the rates of opening the emails were cross-matched with the participants in our SPSS dataset. The gender of the participants was determined by their names and by examining their Facebook profile pictures.

Data analysis plan. In order to test the relations between positive and negative framing, gender, and the interaction between framing and gender on open rates, three Chi-Square tests of independence were conducted. In order to test Hypothesis 1, a Chi-Square test of independence was conducted between positive and negative email framing and open rates. In order to test Hypothesis 2, a Chi-Square test of independence was run between male and female participants and open rates. Finally, in order to test Hypothesis 3, a Chi-Squared test of independence was run between gender and framing on open rate.

Results

Table 1. A Chi-Square test of independence was used to test the effect of positive and negative framing on digital activism. As shown in Table 1, 50% of the participants who received the positively-framed email opened the email and 55.73% of the participants who received the negatively-framed email opened the message. The difference between the frequencies was not significant, X2 (1, N = 384) = 1.265, p = .261.

Table 2. A second Chi-Square test of independence was used to test the effect of gender on digital activism as shown in Table 2. The relation between the two variables was significant, X2 (1, N = 384) = 6.819, p = .009. Specifically, 39% of male participants opened a digital activism email as opposed to 56% of female participants who opened the digital activism email. These proportions suggest that women may be more likely to engage in feminist digital activism, by opening the email.

Table 3. Finally, a third Chi-Square test of independence was used to test the interaction effect between gender and message framing on digital activism as seen in Table 3. In this study, 54.43% of women in the positive campaign opened the email while 58% of women in the negative campaign open the email. In addition, 29.3% of the males in the positive campaign opened the email while 55.3% of the males in the negative campaign opened the email. There was no significant interaction effect between gender and message framing for males, X2 (1, N = 76) = 2.607, p = .106. There was also no significant interaction between female gender and message framing, X2(1, N = 308) = .398, p = .528.

Discussion

Using self-generated email campaigns to assess the relation between framing, gender, and digital activism revealed that women were more likely to open the digital activism email overall. This finding is consistent with both this study’s original hypothesis and previously conducted research (Ellingsen, Johannason, Mollerstorm, & Munkhammar, 2013; Huang & Wang, 2010). While there were no significant findings pertaining to framing and gender and the interaction effect between the three variables, there are a number of limitations regarding this study that need to be addressed so that it can be improved upon in future studies. The method in which gender was assessed may not be completely accurate as some participants’ Facebook profile pictures and/or name may have been misinterpreted by the researcher. In addition, all emails were generated from New York University’s email database, thus inhibiting us from being able to generalize to the public. The unequal gender groups (N=76 Males; N=308 Females), present because of the heavily imbalanced student roster of the program participants were drawn from, could have been improved by quota sampling a more equal population by gender. This would provide for more accurate representation of the difference in response rates between males and females. Furthermore, due to budget and resource restraints, this study utilized emails as an outreach tool for digital activism. However, emailing overall is an ineffective outreach method that garners relatively low response rates across all genders and causes.

In order to circumvent these limitations, future replications can be done through a more effective outreach method such as calling on the phone while using positive and negative framing methods to promote the feminist cause. Researchers could more profoundly explore the degree to which participants were digitally active by measuring whether the participant liked and/or donated to the suggested feminist website. Quota sampling will provide for equal groups of males and females, thus allowing us to obtain fairer result comparisons. Furthermore, it is imperative have a more accurate perception of one’s gender as we could verbally ask how the participant self-identifies.

While this particular study provided only one significant finding, it does attempt to examine how digital activism is influenced by a variety of factors. More specifically, the study examines response differences in not only framing, but also gender and digital activism. Despite substantial amounts of research being conducted on framing effects as a whole, there is still a large gap in literature that fails to examine the variation in responses elicited between different population groups and its effects on different initiatives. This study not only addresses both of these issues, but it also attempts to establish a foundation of empirical evidence for future studies to examine the variation in responses when framing is applied in different populations groups and situations. Furthermore, potential implications regarding this and future studies can significantly contribute to a more efficient method in which we utilize framing to target action-based responses from participants. Through studying the effectiveness of framing on different dimensions, a more comprehensive understanding of how to successfully influence all individual population groups can be achieved.

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