Preferences of Mobile Dating App Users: A Semantic Network Analysis Approach

Abstract

Historically, differences have existed between heterosexual men and women regarding the traits they value most in a potential romantic partner. For example, men have typically prioritized their partner’s physical attractiveness, while women have typically valued job stability and income. These differences in partner selection between men and women have persisted in multiple studies of both traditional dating and online dating, even though other dating norms have changed in the past few decades. The most recent trend in dating is the use of mobile dating apps, but researchers have yet to examine whether these gender differences persist on this new platform. My study attempts to address this information gap by using a semantic network analysis approach combined with frequency distributions to investigate whether gender differences in partner selection are still present when interactions occur via mobile dating apps. Results indicate that men and women value similar attributes when assessing someone’s mobile dating app profile; both groups highly valued potential partners’ physical attractiveness, although women participants using mobile dating apps also prioritized partners’ intelligence and college major. Future research is required to determine whether gender differences in partner preference are disappearing across all forms of dating or if these results are specific to the platform (i.e., the use of a mobile dating app). Because this sample was limited to cisgender college students from a single Midwestern university, future research should also target a more diverse group of participants across age, gender, sexuality, and ethnicity to determine whether these results are generalizable.

 

Jessica Welch is a Ph.D. candidate at Purdue University. She studies communication technology, focusing specifically on social media interactions.

Volume 19, Issue 1 • Fall 2018

 

Throughout history, dating traditions in the United States have evolved through several distinct eras, each with their own set of social norms (Bogle 2008, 12-23). As dating norms have changed, technology has also evolved to meet the public’s demands regarding what type of partner and relationship they desire (Baxter and Cashmore 2013; Bleyer 2014; Naziri 2013; Stampler 2014; Wilson 2014). Many scholars claim that we are currently in the midst of “The Hookup Era,” which is characterized by an increase in casual sexual encounters (Freitas 2013, 19-23; Murstein 1980; Strouse 1987, 75). Dating norms and technologies have changed drastically in the past few decades, but research has found that partner preferences—or what characteristics individuals look for in a potential romantic partner—have remained the same. In both traditional and online dating, men in heterosexual relationships tend to prioritize physical attractiveness while most women value job stability and income (Ahuvia and Adelman 1992,  455; Goetz  2013, 384-85; Jagger 2001, 39; Langlois et. al. 2000, 393; Lechtenberg 2014; Singh 1993, 293). Many scholars have studied these partner preferences in both face-to-face dating and on websites, but no research has examined whether these preferences remain on mobile dating apps.

Beginning with the release of Grindr in 2009 (Bessette 2014), multiple mobile dating apps have been created to meet the needs of on-the-go millennials, who are often more interested in casual and convenient relationships than in serious dating (Baxter and Cashmore 2013; Dredge 2014; Wilson 2014). This mediated dating differs from traditional dating norms by allowing users to “shop” for romantic partners based on specific characteristics, as well as “sell” themselves by promoting their desirable traits, while simultaneously downplaying or omitting their flaws (Heino, Ellison, and Gibbs 2010, 428-29). Additionally, unlike traditional online dating websites with extensive personal profiles, mobile app dating profiles are simple—generally including only a few pictures and a brief biography. This study examines college students’ partner preferences (expressed via mobile dating apps) to determine if today’s heterosexual men and women continue to prioritize different traits when searching for a desirable romantic partner.

 

Literature Review

A Changing Dating Landscape

Bogle (2008) theorizes three distinct eras in dating culture. The first of these, taking place in the early twentieth century, is referred to as “The Calling Era” because it was typical for a man to “call on” a woman of interest and her family. Although love and attraction were important factors during this period, romantic partners were also chosen based on locational convenience and the ability to fulfill traditional gender roles (Bossard 1932, 221-22). Women sought men with stable and well-paying jobs since supporting a family was typically a man’s duty (Bogle 2008, 12-13). On the other hand, men sought women who could produce and raise children, which often translated into women with higher degrees of physical attractiveness. Evolutionary theories indicate that physical attractiveness is a strong predictor of reproductive fitness (Singh, 1993, 293-95; Toma and Hancock 2010, 337-38) and social theories indicate that men often prioritize physical attractiveness due to differences in societal expectations between sexes (Eagly and Wood 1999, 409). Specifically, Social Structural Theory suggests that men and women prefer different partner characteristics because they occupy different roles in society (Eagly and Wood 1999, 412). “The Dating Era,” which took place from the 1920s to the 1960s, was characterized by heterosexual couples going out on dates, generally to restaurants or theaters (Bogle 2008, 13-18). Although leaving the house unaccompanied provided couples with more privacy than that experienced during “The Calling Era,” premarital sex remained uncommon (Bogle 2008). Following “The Dating Era” came “The Partying Era” which began in the 1960s and featured “hanging out” with large groups of friends rather than engaging in the one-on-one dates of the previous era (Bogle 2008, 20-21; Strouse 1987, 375).

Although many dating norms changed throughout these eras, men’s preference for attractive partners and women’s preference for financially stable partners remained constant.

Many scholars argue that, in recent years, society has entered a fourth dating era, commonly referred to as “The Hookup Era” (Bogle 2008, 21-23;  Freitas 2013, 17-34; Glenn and Marquardt 2001; Murstein 1980). Although there is some disagreement on the exact definition of a “hookup,” most scholars agree that, to be considered a hookup, the behavior must be casual, commitment-free, and involve some type of sexual activity (Aubrey and Smith 2013, 435;  Bogle  2008, 25-29; Freitas 2013, 25). Hookup culture stems from a combination of liberalized views of sex and increased instances of partying and alcohol consumption among young people, particularly on college campuses (Bogle 2008, 72-95). Today, casual sex has become more normalized with a 2011 study reporting that 69.9% of participants claimed to have engaged in a hookup (Aubrey and Smith 2013, 439). This differs from previous dating eras in that individuals tend to spend time one-on-one engaging in hookups rather than going on dates or hanging out in groups. One explanation for the replacement of serious dating with casual hangouts and hookups is that the average age for a first marriage is at an all-time high of 27 for women and 29 for men, while the average age of first sexual intercourse is only 17 (Abadi 2018; Gaudette 2017). These more liberalized views of sex particularly impact women, who were stigmatized in the past for engaging in casual and pre-marital sex (Bogle, 2008, 21-22; Gagnon & Simon, 1987, 6-9).

Past Gender Differences

Although dating norms have changed drastically, the differences between what men and women prioritize in potential romantic partners has generally remained consistent. For example, although physical attractiveness is an important factor in the mate-selection process for both genders (Gangestad et. al. 2005, 524-25; Riggio et. al. 1991, 423-24; Singh 2004, 43), men still tend to place more value on it than women (Ahuvia and Adelman 1992, 455; Jagger 2001, 39; Langlois et. al. 2000, 393; Singh 1993, 293; Toma and Hancock 2010, 337- 38). This trend has been true throughout history and is still observable today in online dating (Toma and Hancock 2010, 344-47). For example, women who use a full-body photograph as their profile picture on a dating website receive up to 203% more messages (DatingSiteReviews.com 2015). On the other hand, women—particularly those looking for long-term relationships— tend to place more importance on the careers of their potential partners (Goetz 2013, 384-85). Women tend to especially value men who have jobs that society considers “high status” (like lawyers and doctors) or jobs that society typically codes as masculine (like soldiers or firefighters) (Lechtenberg 2014). Women also typically care more than men about how much money a romantic partner makes (Lechtenberg 2014). Although we know that these gender differences have persisted from traditional dating to online dating, mobile dating apps have yet to be studied from this perspective.

Mobile Dating Apps

In recent years, mobile dating apps have become increasingly popular, especially with the fast-paced millennial generation (Baxter and Cashmore 2013; Dredge 2014; Naziri 2013; Stampler 2014; Wilson 2014). Mobile dating apps differ from online dating in that individuals who use online dating use either a desktop or laptop computer to navigate to a dating website, while mobile dating app users download an app to their phone, making this method more portable. These mobile phone apps utilize G PS to connect individuals to other nearby users and feature a profile with a few pictures and basic demographic information. The first proximity-based dating a pp was called Grindr and was released in 2009 for homosexual men (Bessette 2014). After the creation of Grindr, the popularity of dating apps grew, encouraging some of the most famous dating sites (such as OKCupid) to create accompanying apps. Currently, the most popular dating apps include: Tinder, Bumble, OKCupid, and PlentyOfFish (Laken 2018; Luskinski 2018). When presented with a profile on a dating app, users have the option to indicate interest in that individual in a variety of ways depending on the type of app. For example, Tinder and Bumble feature an interface modeled after a deck of cards where users can “swipe left” (to indicate disinterest) or “swipe right” (to indicate interest) on profiles (Crook 2015).

Additionally, the process for “matching” potential partners differs greatly between mobile app dating and online dating. When creating an account on many subscription-based websites users are required to complete an extensive survey on their interests, personality characteristics, and partner preferences. This information is then used to “match” users who exhibit complementary characteristics; users are typically shown a set number of possible matches per day. On the other hand, potential matches on mobile dating apps are based primarily on proximity. When creating an account, mobile dating app users are not prompted to complete an extensive survey; instead, they are given the option to indicate what gender, age range, and geographical location they are looking for in a romantic partner. Therefore, potential dating app matches are based only on minimal information. Dating apps also generally do not limit the number of matches a user can view per day, which may lead to quicker and more superficial decision-making (Ellison et. al. 2012, 46). Furthermore, because of the limited information available on dating app profiles, users are forced to decide whether they are interested in someone based on only a few attributes. This may encourage an “over- attribution” process wherein subtle cues carry more value because additional cues are not available (Heino, Ellison, and Gibbs 2010, 434-35; Manning 2014, 310; Walther 1996, 17-21).

In combination with new dating platforms like Tinder or Bumble, societal norms regarding casual sex and women’s financial independence have also changed in recent years. A 2012 study found that 29% of women earn a higher income than their husbands (United States Department of Labor 2012) and women currently make up 47% of the United States’ work force (DeWolf 2017).  Because professional and financial independence has become normalized for women, they may be less focused on finding a partner who can financially support them than they were in the past. Furthermore, as casual sex has become destigmatized for women, they may be seeking different types of relationships and prioritizing potential partners’ physical attractiveness more than in past decades.

In light of these changes in technology and societal norms, I aim to examine if and how partner preferences on mobile dating apps potentially reflect a shift from the partner preferences expressed in traditional and online dating. Specifically, this study investigates what characteristics mobile dating app users find most important in their decision to indicate interest in the profile of a potential romantic partner.

RQ1: Are gender differences in partner selection still present when interactions occur via mobile dating apps?

Semantic Network Analysis

One approach that sheds light on this topic is semantic network analysis. This method allows researchers to analyze large datasets and determine patterns in participant responses (Schnegg and Bernard 1996, 7-8). Semantic network analysis creates networks of words that are connected based on their co-occurrence, so words that were used in a single participant’s response will be connected in the network. I chose this method over more traditional methods like content analysis because it allows for easier identification of patterns in participants’ responses. In this study specifically, semantic network analyses were conducted on participant responses to the open-ended questions “What makes you indicate interest in a dating app profile?” and “What makes you indicate disinterest in a dating app profile?” to determine if there are patterns in responses. Semantic network analysis indicates which words co-occur most frequently and if there are clusters of

words that tend to occur together. Results of this analysis demonstrate whether there are typical reasons that participants indicate interest or disinterest on individuals’ mobile dating app profiles. Additionally, semantic network analysis shows whether participants tend to mention certain reasons for indicating interest or disinterest together. For example, participants who mention evidence of alcohol consumption as a reason for indicating disinterest on a profile typically also mention drug use as a deal-breaker. I also use semantic network analysis visualization tools to create visual networks of participant responses, which makes it easier to determine the relationship between individuals’ reasons for indicating interest and disinterest.

Methods

Data Collection

Data was collected in the form of responses to two open-ended questions which were collected via an online Qualtrics survey as part of a larger study on mobile dating app use. Respondents were found using a study participant recruitment system at a large Midwestern university. In order to participate in the study, individuals had to be at least 18 years old, currently attend college, and have had a profile on a mobile dating app at some point. Upon completion of the survey, participants were awarded course credit.

College students were chosen as participants in this study because individuals aged 18– 24 make up the greatest portion of mobile dating app users (Labelle 2018). It is worth noting that college students and non-college students in that age range may use mobile dating apps differently.

Participant Demographics

The survey was completed by 982 participants. Of those 982, 38.4% identified as male, 61.3% as female, and 0.3% as other. Because only three participants identified their gender as other, their responses were removed from further analysis. Therefore, non-binary mobile dating app users are not represented in this sample. One limitation of this study is the homogeneity of the sample. Because participants included only cisgender college students from one Midwestern university, the results may not be generalizable to other populations. The sample was primarily Caucasian with 70.9% of participants identifying as White, 17.9% as Asian or Pacific Islander, 4.9% as Hispanic or Latino, 3.9% as Black or African American, and 2.4% as other. According to the Almanac of Higher Education, the national averages for college students in 4-year, public institutions are: 53.8% Caucasian, 6.9% Asian or Pacific Islander, 15.3% Hispanic, and 10.5% Black (Almanac 2018). Therefore, Caucasian and Asian individuals were overrepresented in this sample and individuals identifying as Hispanic and Black were underrepresented. The majority of participants indicated an age range of 18–24 (99.1%), with seven participants in the 25–30 range and two participants in the 31–36 categories. Participants identified primarily a s heterosexual (94.3%), with 4.1% identifying as bisexual and 1.6% identifying as homosexual. A 2016 study found that 75.9% of women and 88.6% of men aged 18–24 identify as straight, so this sample also underrepresents individuals who self- identify as LGBTQ (Copen 2016, 3).

Formatting Data

The dataset includes 982 responses to the questions “What makes you indicate interest in a dating app profile?” and “What makes you indicate disinterest in a dating app profile?” Data for each question was divided by identified sex, creating four files: “women indicate disinterest,” “women indicate interest,” “men indicate disinterest,” and “men indicate interest.” This was done so that responses from men and women could be analyzed separately to find differences in the responses.

Data Analysis

Each of the four files were uploaded to the network analysis tool AutoMap to undergo preprocessing, including spelling corrections and the deletion of noise words like “the,” “a,” and “an.” Co-reference lists and concept lists were generated and uploaded to a visualization tool called NodeXL. Concept lists included words that occurred most frequently (more than 10 times) and co- reference lists included words that were mentioned together by participants two or more times. In the visualization the frequency with which pairs of words co- occurred was represented by edge width and how often individual words were mentioned is illustrated by node size. The Harel-Koren Fast Multiscale algorithm (Harel and Koren 2002, 187-90) was used to lay out the graphs and nodes were grouped by cluster using the Clauset-Newman-Moore (2004, 1-4) algorithm (see Figures 1-4). Nodes represent the words participants used in their responses to the two questions. Edges indicate that a pair of words was mentioned by a single participant. Loops in the graph indicate that a word was mentioned in the same response twice. Finally, words that were grouped in the same cluster often occurred together, indicating that participants who mentioned one of those words typically mentioned the others.

A variety of node-level metrics were calculated to answer the research question. The node-level metrics included: degree centrality, betweenness centrality, and Eigenvector centrality. See Table 1 for an explanation of these metrics and their implications in this context.

In general, a word with high degree centrality, betweenness centrality, and Eigenvector centrality is a word that is important to the network, indicating that it is a significant reason participants gave for indicating interest or disinterest on a mobile dating app profile.

Results

Women Indicate Disinterest

Degree centrality, betweenness centrality, and Eigenvector centrality metrics were calculated for the “women indicate disinterest” dataset. “Picture” had the highest metrics for each with a degree centrality of 13, a betweenness centrality of 100, and an Eigenvector centrality of 0.24. “Picture” was also the most frequently-occurring word, with 214 mentions by participants. (See Figure 5 for the “picture” ego network).

Men Indicate Disinterest

The most important word in the “men indicate disinterest” dataset was more difficult to determine with “grammar,” “picture,” and “tattoo” all having the same metrics (degree centrality=2; betweenness centrality=1; eigenvector centrality=0.11). Because this network was less dense (less connected) than the others,  frequency of word occurrence was also considered. The individual word that appeared most frequently was “picture,” with 75 mentions. “Not physically” and “attractive” were the pair that occurred the most, with 124 mentions. Therefore, it was concluded that “picture” and “not physically attractive” were the most important aspects of this network. See Figures 6 and 7 for their ego networks.

The most common reasons for indicating disinterest on dating app profiles are the same for men and women, but some of the more minor reasons differ. “Picture” was one of the primary reasons that both genders claim to indicate disinterest on a profile, with men mentioning profile pictures in general and women discussing specific negative aspects of pictures, like low-quality and shirtless pictures. Both genders also agree on some of the more minor reasons for indicating disinterest, such as age, bad spelling and grammar, and smoking or drug use. Women particularly mention being uninterested in individuals involved in Greek life or who seem like “party animals” (See Figures 1 and 2).

Low physical attractiveness seems to be more of a deal-breaker for men, with “not physically attractive” being mentioned many times ,along with “hair color” and “duck face.” Women also cite low physical attractiveness as a reason for indicating disinterest, but to a lesser degree, with women mentioning “not physically attractive” approximately one tenth as many times as men. Political affiliation seems to play a role in both genders’ decision to indicate disinterest, with men saying that they express disinterest in “liberal” individuals while women claim to express disinterest in profiles that include confederate flags.

Women Indicate Interest

The word “attractive” played a significant role in this network with the highest score in each metric. (degree centrality=16; betweenness centrality=244.58; Eigenvector centrality=0.16). “Attractive” also occurred most frequently in these responses, being mentioned by participants 174 times. (See Figure 8 for the “attractive” ego network).

Men Indicate Interest

“Attractive” also had the highest scores in each of the three metrics run for the “men indicate interest” network (degree centrality=8; betweenness centrality=19; Eigenvector centrality=0.30). “Attractive” was the most frequently mentioned word in this dataset, with 122 mentions. (See Figure 9 for the “attractive” ego network).

Both genders agree on their primary reasons for expressing interest in dating profiles but differ in some of the more minor reasons. For both men and women, physical attractiveness was the main reason for indicating interest. While both genders mentioned the importance of attractiveness, men emphasized their desire for physically fit partners, while women expressed their preference for tall individuals. Both genders also value partners who are funny and share their interests and hobbies (See Figures 3 and 4).

One difference between genders is that men mentioned expressing interest in individuals who seemed to have a “good personality” while women expressed interest in intelligent partners. Women also claimed to indicate interest in individuals expressing a desire for a serious relationship. Finally, women mentioned individuals’ major or occupation as a reason to indicate interest, while men did not.

Discussion

This study makes several contributions to the topics of modern dating preferences and technology use. Most significantly, it offers a way to explicate a new understanding of the use of mobile dating apps through users’ tendencies to indicate interest or disinterest in certain attributes.

Deal-makers

Results indicate that both men and women focus primarily on physical attractiveness when deciding whether they are interested in an individual’s dating profile. While both genders value attractiveness, women tend to prefer tall partners while men seem partial to individuals who are physically fit (See Figures 3 and 4). This emphasis on physical attractiveness for both genders may be explained by the nature of mobile dating apps. Because the profiles contain so little information about each user, pictures are the major cue individuals use to determine whether they are interested in someone. Individuals’ motivation for using a dating app likely also plays a role. For example, men and women primarily interested in casual sexual experiences may prioritize physical attractiveness above all other attributes.

On the other hand, women mentioned that an individual’s college major and intelligence level plays a role in their decision to indicate interest, while men did not mention either of these factors. Past research found that women tend to value a potential partner’s current job stability and income. Although they are still in college, female participants did mention “occupation” as a factor for expressing interest almost seven times as often as men, indicating that the college women in this sample place more importance on their partner’s future income and profession than their male counterparts do.

There are a few possible explanations for this result. One possibility is that, because of cultural gender norms, men tend to include information related to their current job or major in their profile while women do not. If this is the case, men do not mention women’s jobs or majors as a factor in their romantic decision-making simply because this information is less likely to be available. Another explanation could be related to women’s tendency to express interest in men who appear to offer the potential for a longer-term relationship. Previous research (Goetz 2013, 384-85) found that women interested in long-term relationships place greater value on potential partners’ job stability and ability to acquire resources. Therefore, if women sometimes use dating apps to find serious relationships but men do not, that might explain why women tend to place a higher value on their partners’ intended or current occupation.

Deal-Breakers

When asked what qualities make them lose interest in a dating app profile, men and women had many similar responses. Both genders said that any smoking or drug use was a deal breaker, as is grammar or spelling errors (See Figures 1 and 2). This emphasis on grammar and spelling may be a symptom of the sample. Because participants all attend an elite university, they may be more concerned with these elements than an average mobile dating app user.

Several elements of the dating profile itself can also be deal-breakers. First, both men and women lose interest in profiles with “group pictures” (pictures of multiple people). Upon closer inspection of the original text, it became clear that many individuals dislike group pictures because they make it difficult to determine to whom the profile belongs. Women appear to be more particular than men about which pictures are included in dating profiles, mentioning mirror pictures (pictures taken in a mirror’s reflection) and low-quality pictures as additional reasons to lose interest.

Limitations and Future Research

Despite this study’s contributions to the understanding of dating app preferences, it still presents several limitations that future research could address. The first limitation relates to the study participants. Although I conducted this study at a large and moderately diverse school, the sample included only cisgender college students at a single Midwestern university. It is possible that the gender differences in partner preference from previous eras may be more present among older mobile dating app users, as they are more likely to be looking for long-term partners. Furthermore, the majority of participants identified as Caucasian and heterosexual, leaving individuals of different ethnicities and sexualities underrepresented. Individuals of varying races and sexual orientations may use other dating apps and behave differently on those apps. Future research should examine a more diverse group of individuals to determine if and how they differ.

Another limitation is that it is impossible to determine if both genders value attractiveness equally because of the nature of dating apps and their simplistic profiles, and/or because changes are occurring in the dating landscape itself, and/or because individuals use these apps to find sexual partners rather than romantic partners. The increasing acceptance of casual sex and the prevalence of hookups on college campuses may encourage mobile dating app users to seek sexual relationships rather than long- term relationships. If that is the case, it makes sense for physical attractiveness to be a top priority for both men and women users because they do not plan to be with that partner for the long-term. Additional research is needed to determine whether the mobile dating app platform itself encourages users to prioritize physical attractiveness or if a shift in men and women’s current values have led to the emphasis on evaluating physical attractiveness regardless of the dating method involved.

Furthermore, although mobile dating apps were designed to help individuals find romantic partners, people also use them in other ways. A 2017 study on individuals’ motivations for using Tinder found that Tinder users do not exclusively use the app to find relational or sexual partners (Timmermans and De Caluwe 2017, 341). Another study developed a scale measuring why individuals use mobile dating apps and found that some mobile dating app users are looking for validation or entertainment in addition to seeking sexual and romantic partners (Welch and Morgan 2018, 112). Because individuals use dating apps for a variety of reasons, it may be that an individual’s motivation for using the app affects what attributes they prioritize. For example, a user looking for a serious relationship may be interested in different profiles than an individual using the app for casual sex. Future research should investigate how users’ motivations impact their preferences.

Conclusion

Although past research indicates that men and women differ significantly in their preference of romantic partners’ characteristics, the results of the current study indicate that—on mobile dating apps—these preferences are more similar than they are different. While women seem to value intelligence and college major more than men, both genders strongly consider physical attractiveness in their decision to express interest or disinterest in a potential romantic partner. This finding may be explained by the cultural shift to The Hookup Era in which a partner’s physical attractiveness is most important because of the nature of the relationship. The age at which people get married is also increasing, so college students likely do not feel pressure to find “the one” and may use dating apps to explore other types of relationships (in contrast to older generations that got married much younger). On the other hand, the results may be purely because of the design of mobile dating apps, which tend to highlight physical attractiveness, above all other attributes. Past research (Timmermans and De Caluwe 2017, 341; Welch and Morgan 2018, 112) has found that individuals vary in their motivations for using mobile dating apps, so that may play a role in their preferences as well. Future research should aim to determine whether partner preferences across all forms of dating are changing, or if new technologies like mobile apps are changing our partner preferences only when we use them.

This research contributes to the literature by examining heterosexual men and women’s partner preferences in the midst of changing dating social norms while using a relatively new dating technology. To improve the generalizability of results, future studies should include a sample that is more diverse in terms of participants’ age, gender, sexuality, and ethnicity. Nonetheless, results of this study pave the way for future researchers to examine how cultural norms, mobile dating app interfaces, and user motivations impact individuals’ partner preferences.

Figure 1. Women Indicate Disinterest Semantic Network

Figure 2. Women Indicate Interest Semantic Network

Figure 3. Men Indicate Disinterest Semantic Network

Figure 4. Men Indicate Interest Semantic Network

Figure 5. Ego Network for “Picture” from the Women Indicate Disinterest Network.

Figure 6. Ego Network for “Picture” from the Men Indicate Disinterest Network.

Figure 7. Ego Network for “Not Physically Attractive” from the Men Indicate Disinterest Network.

Figure 8. Ego Network for “Attractive” from the Women Indicate Interest Network.

 

 

Figure 9. Ego Network for “Attractive” from the Men Indicate Interest Network.

 

Bibliography

Abadi,Mark.2018.“7ThingstheAverageAmericanhasAccomplishedbyAge35.”Business Insider,June7,2018.https://www.businessinsider.com/average-age-married-home-

job-35-2018-6.

Ahuvia, Aaron C., and Mara B.Adelman. 1992. “Formal Intermediaries in the Marriage Market: A Typology and Review.” Journal of Marriage and the Family 54(2): 452-63.

Aubrey, Jennifer Stevens, and Siobhan E. Smith. 2013. “Development and Validation of the Endorsement of the Hookup Culture Index.” Journal of Sex Research 50(5): 435-48.

Baxter, Holly, and Pete Cashmore. 2013. “Tinder: The Shallowest Dating App Ever?” The Guardian, November 23, 2013. https://www.theguardian.com/lifeandstyle/2013/nov/23/tinder-shallowest-dating-app-ever.

Bessette, Chanelle. 2014. “10 Questions: Joel Simkhai, Founder and CEO, Grindr.” Fortune, August 12, 2014. http://fortune.com/2014/08/12/10-questions-joel-simkhai-founder-and-ceo-grindr/.

Bleyer,Jennifer.2014.“Dating:LovetheOneYou’reNear.”PsychologyToday,July1,2014.https:// www.psychologytoday.com/us/articles/201407/dating-love-the-one-youre-near.

Bogle, Kathleen A. 2008. Hooking Up: Sex, Dating, and Relationships on Campus. New York, New York: New YorkUniversity Press.

Bossard, James H.S. 1932. “Residential Propinquity as a Factor in Marriage Selection.” American Journal of Sociology 38 (2): 219-24.

Clauset, Aaron, and Mark E.J. Newman, and Cristopher Moore. 2004. “Finding Community Structure in Very Large Networks.” Physical Review 70 (6): 1-6.

Copen,Casey. 2016. “Health National Statistics Report.” Health Statistics, 88:1–14,https://www.cdc.gov/nchs/data/nhsr/nhsr088.pdf.

Crook, Jordan. 2015. “Hate It or Love It, Tinder’s Right Swipe Limit is Working.” TechCrunch. com (blog). March 2, 2015 https://techcrunch.com/2015/03/12/hate-it-or-love-it-tinders-right- swipe-limit-is-working/#.mxw5lv:jC0w.

DeWolf, Mark. 2107. “12 Stats aboutWorking Women.” U.S. Department of Labor (website). https://blog.dol.gov/2017/03/01/12-stats-about-working-women.

Dredge,Stuart.2014.“Tinder:The’PainfullyHonest’DatingAppwithWiderSocialAmbitions.” TheGuardian,February23,2014.https://www.theguardian.com/technology/2014/feb/24/tinder-dating-app-social-networks.

Eagly, Alice H., and Wendy Wood. 1999. “The Origins of Sex Differences in Human Behavior: Evolved Dispositions versus Social Roles.” American Psychologist 54 (6): 408-23.

Ellison, Nicole B., Jeffrey T. Hancock, and Catalina L. Toma. 2012. “Profile as Promise: A Framework for Conceptualizing Veracity in Online Dating Self-Presentations.” New Media & Society 14(1): 45-62.

Freitas, Donna. 2013. The End of Sex:How Hookup Culture is Leaving a GenerationUnhappy, Sexually Unfulfilled and Confused about Intimacy. New York, New York: Basic Books.

Gagnon, John H. and William Simon. 1987. “The Sexual Scripting of Oral Genital Contacts.”

Archives of Sexual Behavior 16 (1): 1-25.

Gangestad,StevenW.,andGlennJ.Scheyd.2005.“TheEvolutionofHumanPhysical Attractiveness.” Annual Review of Anthropology 34 (1):523-48.

Gaudette, Emily. 2017. “When and How do Most Americans Lose their Virginity?” Inverse. https://www.inverse.com/article/32446-sex-first-time-virginity-age.

 

Goetz, Cari D. 2013. “What Do Women’s Advertised Mate Preferences Reveal? An Analysis of Video Dating Profiles.” Evolutionary Psychology 11 (2): 383-91.

Harel, David, and Yehuda Koren. 2000. “AFast Multi-Scale Method for Drawing Large Graphs.” In International Symposium on Graph Drawing, 183-196. Berlin, Heidelberg: Springer.

Heino, Rebecca D., Nicole B. Ellison, and Jennifer L. Gibbs. 2010. “Relationshopping: Investigating the Market Metaphor in Online Dating.” Journal of Social and Personal relationships27 (4): 427-47.

Jagger, Elizabeth. 2001. “Marketing Molly and Melville: Dating in a Postmodern, Consumer Society.” Sociology35 (1): 39-57.

Labelle, Brandon. 2018. “AnotherTech Gender Gap: A Dating App Breakdown.” Apptopia (blog), February 9, 2018. http://blog.apptopia.com/dating-apps-male-dominated.

“Labor Force Participation.” 2012. United States Department of Labor (website). https://www.dol. gov/wb/stats/mother_families.htm.

Laken, Howard. 2018. “6 Most Popular Dating Apps for Millennials in 2018.” Bustle.com (blog) June 6, 2018. https://www.bustle.com/p/6-most-popular-dating-apps-for-millennials-in-2018-9301722.

Langlois, Judith H., Lisa Kalakanis, Adam J. Rubenstein, Andrea Larson, Monica Hallam, and Monica Smoot. 2000. “Maxims or Myths of Beauty? A Meta-Analytic and Theoretical Review.” Psychological Bulletin 126 (3): 390-423.

Lechtenberg,Suzie.2014.“WhatYouDon’t Know AboutOnline Dating.”Freakonomics(podcast) February6,2014.http://freakonomics.com/podcast/what-you-dont-know-about-online-dating-a-new-freakonomics-radio-podcast/.

Lusinski, Natalia. 2018. “The Most Popular Dating Apps in 2018 Among Singles in America.” Bustle.com (blog) February 2, 2018. https://www.bustle.com/p/the-most-popular-dating-apps-in-2018-among-singles-in-america-8105619.

Manning, Jimmie. 2014. “Construction of Values in Online and Offline Dating Discourses: Comparing Presentational and Articulated Rhetoric of Relationship Seeking.” Journal of Computer-Mediated Communication 19 (3): 309-324.

Naziri, Jessica. 2013. “Start-up Sunday: Tinder Aims to Make Dating Easier.” Los Angeles Times, March 10, 2013. http://articles.latimes.com/2013/mar/10/business/la-fi-tn-tinder-dating-app-startup-20130306.

Riggio,RonaldE.,KeithF.Widaman,Joan S.Tucker,andCharlesSalinas.1991.“BeautyisMore than Skin Deep: Components of Attractiveness.” Basic and Applied Social Psychology 12 (4):423- 439.

Schnegg,Michael,andH.RussellBernard.1996.“Wordsasactors:AMethodforDoingSemantic Network Analysis.” CAM Journal8(2):7-10.

Singh, Devendra. 1993. “AdaptiveSignificance of Female Physical Attractiveness: Role of Waist- to-Hip Ratio.” Journal of Personality and Social Psychology 65(2): 293-307.

Singh, Devendra. 2004. “Mating Strategies of Young Women: Role of Physical Attractiveness.”

Journal of Sex Research 41 (1): 43-54.

Stampler,Laura.2014.“InsideTinder:Meet the GuysWhoTurnedDating Into an Addiction.” Time (magazine) February 6, 2014.http://time.com/4837/tinder-meet-the-guys-who-turned-dating-into-an-addiction/.

Strouse,JeremiahS.1987.“CollegeBarsasSocialSettingsforHeterosexualContacts.”TheJournal of Sex Research 23(3):374-82.

 

“StudentsbyGender,Race,andEthnicity,bySector,Fall2010andFall2016.”2018.Almanac. https://www-chronicle-com.ezproxy.lib.purdue.edu/article/Students-by-Gender-Race- and/244003?cid=cp216.

Timmermans,Elisabeth,andElienDeCaluwé.2017.“DevelopmentandValidationoftheTinder Motives Scale (TMS).” Computers in Human Behavior 70:341-50.

Toma, Catalina L., and Jeffrey T. Hancock. 2010. “Looks and Lies: The Role of Physical Attractiveness in Online Dating Self-Presentation and Deception.” Communication Research 37 (3): 335-51.

Walther, Joseph B. 1996. “Computer-Mediated Communication: Impersonal, Interpersonal, and Hyperpersonal Interaction.” Communication Research 23 (1): 3-43.

Welch, Jessica R., and Melanie Morgan. 2018. “Development and Validation of the Mobile Dating App Gratification Scale: Effects of Sought Gratifications on User Behavior and Outcomes.” Communication, Society, and Media 1 (2): 108-24.

Wilson, Rebecca. 2014. “Sexperts: Tinder App Women Dating Power.” The Sandspur, March27, 2014. http://www.thesandspur.org/sexperts-tinder-app-affords-women-dating-power/.

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