Older adults are utilizing online dating websites in increasing numbers. Theories addressing age-related changes in motivation suggest that younger adults are likely to emphasize themselves, achievements, attractiveness, and sexuality.
Older adults are likely to present themselves positively and emphasize their existing relationships and health. We collected 4, dating profiles from two popular websites to examine age differences in self-presentations. We used stratified sampling to obtain a sample equally divided by gender, aged 18—95 years. Regression analyses revealed that older adults were more likely to use first-person plural pronouns e. Younger adults were more likely to use first-person singular pronouns e.
In contrast, older adults are more positive in their profiles and focus more on connectedness and relationships to others. Indeed, popular media report that more older adults are finding dates online Watson, with one source claiming that adults aged 60 and older represent the largest growing segment of adults using online dating websites Ellin, Few studies have examined age differences in dating self-presentations e.
A systematic quantitative analysis of the language adults use in dating profiles may further illuminate motivations to date at different ages. Adults of all ages may share certain motivations to date, including companionship and romance. However, adults of different ages have distinct goals, priorities, and motivations, which their self-presentations to potential dating partners may convey.
Predictions in this study were derived from three key theories—sociocultural theories, evolutionary theory, and socioemotional selectivity theory. Collectively, these theories suggest that people of different ages may present themselves in distinct ways when seeking romantic partners.
In contrast, in late life, individuals may seek romantic partners who can become a part of their established social world. Moreover, as they age, adults concentrate on connections to family, viewing themselves in a communal context Fingerman, Based on a lifetime of investment, ties to family and friends are of heightened importance to older adults Blieszner, Indeed, the language people use when constructing their self-presentations may convey such differences.
We also examined gender differences in these patterns. Elsewhere, Groom and Pennebaker examined online dating profiles of younger adults and found that women were more likely to use pronouns especially first-person singular than were men. Sexuality, Reproduction, and Health Evolutionary theories posit that gender roles have evolved, such that men and women select for different qualities when choosing a partner Buss, Studies using evolutionary theory highlight different mate selection strategies for men and women, reflecting gender differences in reproduction and parental investment.
Although most studies examining evolutionary theory and mate selection have been limited to young adults of reproductive age e. Health also is more self-relevant for older adults, as they are more likely to suffer health problems than younger adults.
Older adults also may be concerned with presenting their involvement in exercise and physical activity, so as not to appear frail. As such, older men may be most likely to describe their health when presenting themselves to a potential romantic partner.
Work, Status, and Achievement Achievements and status also may be key themes in self-presentations. Through early midlife, individuals focus on attaining roles necessary for a successful adult life by pursuing an education, building a career, seeking marriage, and becoming a parent Cherlin, ; Furstenberg, As such, younger adults may be concerned with presenting themselves in terms of their careers and accomplishments.
Self-presentations indicating status may not show age differences, however. Evolutionary theory suggests that adults are likely to highlight attributes indicative of higher mate value. For men especially, mate value is conceptualized in terms of status, reflecting an ability to provide for future offspring Buss, , Alterovitz and Mendelsohn used content analysis to examine dating profiles from people aged 20 to more than 75 years.
Older women emphasized desiring status in a partner, whereas older men offered more status-related information about themselves.
Furthermore, research suggests that older women are particularly concerned with financial independence; therefore, older men may be more inclined to address money when seeking a partner in order to assuage concerns related to financial dependency Dickson et al. Socioemotional Motivations We also considered socioemotional motivations in dating profiles. Thus, older adults may be more likely to present themselves in positive terms than younger adults. This is not to say that we expected young adults to present themselves negatively, but rather, older adults may be more likely to focus on positive aspects of what they bring to a dating relationship, particularly positive emotions.
Overview of the Current Study The current study involved a systematic analysis of the language used by adults of different ages in the text of online dating profiles. Data from online dating profiles offered an ecologically valid way to examine age differences in self-presentations. We also considered geographic location and ethnic differences. To examine a national sample of dating profiles, we drew samples from five major metropolitan areas encompassing urban, suburban, and rural outlying areas from across the United States.
Prior research has not addressed geographic or ethnic differences in dating motivations, but they were considered in the current study. In summary, we expected the following patterns regarding age differences in online profiles.
Compared with younger adults, older adults will use a higher proportion of words in the following categories: Compared with younger adults, older adults will use a lower proportion of words in the following categories: We did not have strong age-by-gender predictions, but considered possible gender differences in each of these patterns.
Method Source of Online Dating Profiles The sample of dating profiles was drawn from two major dating websites. We identified these websites using search engines e. We also limited the study to dating websites that allow users to search for potential partners rather than assigning a limited array of partners; e. After exclusions, two popular websites remained. There was no charge for creating a profile on either website, but one of the websites charged to connect with a potential dating partner.
Users completed an optional free response section i. The instructions to create the free response section differed among the websites. We did not collect profiles that contained fewer than 30 words; potential profiles from a random sampling described in Participants were excluded due to responses with fewer than 30 words.
Participants The study included 4, profiles, 2, sampled from each of the online dating websites using random quota sampling without replacement.
Within each website, we collected 1, profiles from heterosexual males and 1, profiles from heterosexual females. Users search for profiles via geographic location, age, and gender filters. To ensure a geographic dispersion of profiles, we selected equal numbers of profiles from five major metropolitan areas including urban, suburban, and rural areas: We randomly selected zip codes from each of the five areas to search for profiles.
Within each zip code, for each gender, we then randomly selected profiles among four age groups: We used these stratifications to assure a full age range of dating profiles in sampling. Because the older adults group could incorporate up to 30 years, we treated age as a continuous variable rather than as a grouping variable in analyses.
From each profile, we extracted: To assure anonymity of profile writers, we did not obtain additional demographic information e. The sampling method is illustrated in Supplementary Appendix A. The sample ranged in age from 18 to 95 years. This software calculates the frequency and proportions of specific categories of words within a text file. The LIWC program compares each word of a text file with an internal dictionary of more than 4, words assigned to word categories. This study drew on 11 established LIWC categories: