Two-sided matching markets are a cornerstone of modern economics. They model a wide range of applications such as ride-sharing, online dating, job positioning, school admissions, and many more. In many of those markets, monetary exchange does not play a role. For instance, the New York City public high school system is free of charge. Thus, the decision on how eighth-graders are assigned to public high schools must be made using concepts of fairness rather than price. There has been therefore a huge amount of literature, mostly in the economics community, defining various concepts of fairness in different settings and showing the existence of matchings that satisfy these fairness conditions. Those concepts have enjoyed wide-spread success, inside and outside academia. However, finding such matchings is as important as showing their existence. Moreover, it is crucial to have fast (i.e., polynomial-time) algorithms as the size of the markets grows. In many cases, modern algorithmic tools must be employed to tackle the intractability issues arising from the big data era. The aim of my research is to provide mathematically rigorous and provably fast algorithms to find solutions that extend and improve over a well-studied concept of fairness in two-sided markets known as stability. This concept was initially employed by the National Resident Matching Program in assigning medical doctors to hospitals, and is now widely used, for instance, by cities in the US for assigning students to public high schools and by certain refugee agencies to relocate asylum seekers. In the classical model, a stable matching can be found efficiently using the renowned deferred acceptance algorithm by Gale and Shapley. However, stability by itself does not take care of important concerns that arose recently, some of which were featured in national newspapers. Some examples are: how can we make sure students get admitted to the best school they deserve, and how can we enforce diversity in a cohort of students? By building on known and new tools from Mathematical Programming, Combinatorial Optimization, and Order Theory, my goal is to provide fast algorithms to answer questions like those above, and test them on real-world data. In Chapter 1, I introduce the stable matching problem and related concepts, as well as its applications in different markets. In Chapter 2, we investigate two extensions introduced in the framework of school choice that aim at finding an assignment that is more favorable to students -- legal assignments and the Efficiency Adjusted Deferred Acceptance Mechanism (EADAM) -- through the lens of classical theory of stable matchings. We prove that the set of legal assignments is exactly the set of stable assignments in another instance. Our result implies that essentially all optimization problems over the set of legal assignments can be solved within the same time bound needed for solving it over the set of stable assignments. We also give an algorithm that obtains the assignment output of EADAM. Our algorithm has the same running time as that of the deferred acceptance algorithm, hence largely improving in both theory and practice over known algorithms. In Chapter 3, we introduce a property of distributive lattices, which we term as affine representability, and show its role in efficiently solving linear optimization problems over the elements of a distributive lattice, as well as describing the convex hull of the characteristic vectors of the lattice elements. We apply this concept to the stable matching model with path-independent quota-filling choice functions, thus giving efficient algorithms and a compact polyhedral description for this model. Such choice functions can be used to model many complex real-world decision rules that are not captured by the classical model, such as those with diversity concerns. To the best of our knowledge, this model generalizes all those for which similar results were known, and our paper is the first that proposes efficient algorithms for stable matchings with choice functions, beyond classical extensions of the Deferred Acceptance algorithm. In Chapter 4, we study the discovery program (DISC), which is an affirmative action policy used by the New York City Department of Education (NYC DOE) for specialized high schools; and explore two other affirmative action policies that can be used to minimally modify and improve the discovery program: the minority reserve (MR) and the joint-seat allocation (JSA) mechanism. Although the discovery program is beneficial in increasing the number of admissions for disadvantaged students, our empirical analysis of the student-school matches from the 12 recent academic years (2005-06 to 2016-17) shows that about 950 in-group blocking pairs were created each year amongst disadvantaged group of students, impacting about 650 disadvantaged students every year. Moreover, we find that this program usually benefits lower-performing disadvantaged students more than top-performing disadvantaged students (in terms of the ranking of their assigned schools), thus unintentionally creating an incentive to under-perform. On the contrary, we show, theoretically by employing choice functions, that (i) both MR and JSA result in no in-group blocking pairs, and (ii) JSA is weakly group strategy-proof, ensures that at least one disadvantaged is not worse off, and when reservation quotas are carefully chosen then no disadvantaged student is worse-off. We show that each of these properties is not satisfied by DISC. In the general setting, we show that there is no clear winner in terms of the matchings provided by DISC, JSA, and MR, from the perspective of disadvantaged students. We however characterize a condition for markets, that we term high competitiveness, where JSA dominates MR for disadvantaged students. This condition is verified, in particular, in certain markets when there is a higher demand for seats than supply, and the performances of disadvantaged students are significantly lower than that of advantaged students. Data from NYC DOE satisfy the high competitiveness condition, and for this dataset our empirical results corroborate our theoretical predictions, showing the superiority of JSA. We believe that the discovery program, and more generally affirmative action mechanisms, can be changed for the better by implementing the JSA mechanism, leading to incentives for the top-performing disadvantaged students while providing many benefits of the affirmative action program.

This study explores online dating by studying the relationship between self-disclosure and self-efficacy in an online dating environment. This research study examines the way self-disclosure, self-efficacy, self-esteem, and gender interrelate in an online dating environment. This study includes, but is not limited to, discussion of the type of correlation between self-efficacy and self-esteem, the relationship between self-disclosure and self-efficacy, and the differences between men's and women's self-disclosure in an online dating environment. From conducting this study, the researcher was able to determine that there is a statistically significant relationship between gender and how it relates to self-disclosure and self-efficacy. With the results from the study, the understanding of how different variables relate to online dating and romantic relationships has been taken one step further as it helps fill the gap in the literature.

Denna studie kommer presentera resultatet av en kvantitativ undersökning där syftet var att se om Tinderanvändning påverkar individers självkänsla och om påverkan är beroende av genus. Datainsamlingen genomfördes med en online-enkät över Facebook där 102 respondenter deltog (K = 55 och M = 47). Användares uppskattade tid på Tinder var huvudvariabeln inom Tinderanvändning i denna studie och forskarna konstruerade egna frågor för att kontrollera tidsfrekvensen. För att kontrollera bakomliggande faktorer inom Tinderanvändning konstruerade forskarna egna frågor för att undersöka profilnöjdhet, Tindernöjdhet, glädje efter Tinder, högersvep och matchningar. Självkänsla mättes genom Rosenberg självkänsloformulär. Utifrån Festingers teori om social jämförelse konstruerades tre frågor om social jämförelse på Tinder. Resultatet visade att hypotes 1 Tinderanvändning har en negativ påverkan på mäns självkänsla och 2 Tinderanvändning har en positiv påverkan på kvinnors självkänsla inte stämmer, studien kunde inte bekräfta att huvudvariabeln tidsfrekvens har en påverkan på män och kvinnors självkänsla. Studien kunde fastställa att variabeln profilnöjdhet har en signifikant positiv påverkan på män och kvinnors självkänsla och det upptäcktes en könsskillnad där män påverkas starkare av profilnöjdheten. / This study will present the results of a quantitative survey where the aim was to see if Tinder use affects individuals' self-esteem and if the effect is dependent on gender. The data collection was carried out with an online survey via Facebook in which 102 respondents participated (F = 55 and M = 47). The user's estimated time on Tinder was the main variable of Tinder use in this study and the researchers constructed their own questions to control for time frequency. To control for underlying factors in Tinder use, the researchers constructed their own questions to examine profile satisfaction, Tinder satisfaction, happiness after Tinder, right swipes, and matches. Self-esteem was measured by the Rosenberg self-esteem scale. Based on Festinger's theory of social comparison, three questions about social comparison on Tinder were constructed. The result showed that hypotheses 1 Tinder use has a negative effect on men's self-esteem and 2 Tinder use has a positive effect on women's self-esteem are not true, the study could not confirm that the main variable time frequency has an impact on men's and women's self-esteem. The study was able to determine that the profile satisfaction variable has a significant positive impact on men's and women's self-esteem and a gender difference was discovered where men are more strongly affected by profile satisfaction.

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This thesis aims to map and describe how users of online dating servers use this medium. How do they self-present on dating sites and how do they create a profile. What is the motivation to use the online dating sites. For data collection, I chose qualitative research. As a qualitative method were used depth interviews with fourteen users of dating site Badoo. The work is divided into two parts. The first part will focus on theoretical concepts. Detail is devoted to the history of online dating, self-presentation, motivation to use online dating sites. Furthermore, the theoretical approaches discussed the relations in terms of evolutionary psychology and, ultimately, stereotypes. The second part is empirical. It deals with methodology, research questions, research strategies and especially the analysis of interviews. Based on interviews with respondents, I have developed several key categories, which are described in more detail the analytical part. This study describes the attitudes/ approach of respondents to categories such as motivation to use dating sites, self-presentation, communication and stereotypes which I have noticed in my research sample. The last part is devoted to a summary of findings and research results.

While a growing body of literature exists examining how intersecting social identities and structural organizations shape the on-campus hookup script, research examining the impact of technology on the hookup culture has been virtually nonexistent. Addressing this gap, this study adds to a current body of literature on the hookup culture and online dating by exploring how a diverse sample of young women and non-binary, femme individuals understand and negotiate interpersonal sexual scripts through the mobile dating app Tinder. Ultimately, findings from 25 in-depth interviews reveal how Tinder has shaped the sexual scripts of young adult dating into a "hybrid hookup script." Unlike the traditional college hookup culture, which centers the hookup script on fraternity parties, sexual dancing, and drinking, the hybrid hookup script reintroduces traditional dating practices, such as formal dates, into the modern sexual scripts of young adults. Specifically, the hybrid hookup script maintains the traditional gendered expectation that men initiate conversations and dates, while incorporating the patterns of drinking and the expectation of non-relational sex central to the on-campus hookup culture. Nearly all participants engaged in the hybrid hookup script to some extent; yet, women of color were overrepresented among those who eventually opted out of Tinder altogether. In particular, experiences of sexual and racial harassment created an environment in which women of color felt racially objectified and fetishized. As a result, the majority of women of color indicated that they deleted the app and did not intend to go back. Overall, results underscore how the Tinder app may be operating to rearticulate existing hierarchies of gender and race.

近年來平台商業模式與網路交友的盛行，使得許多網路交友平台應運而生。平台的收費模式不以傳統使用者付費的觀念建立，而是以整體平台的互動作為收費的考量，以較優惠或是免費的方式來吸引會引起正向跨邊網路效應的使用者加入，讓他們作為平台的被補貼方，藉此吸引平台的付費方群體加入。 本研究以雙邊平台的觀點來研究網路交友平台是如何設計讓使用者願意加入此平台、如何設計互動機制讓平台上雙方群體進行互動，如何訂定合適的管制讓使用者能方便使用並信任此平台上使用者的真實性，讓適當的顧客匯集。即使同為網路交友平台，其交友的目的、交友的模式也有所不同，因此本研究先探討各交友平台是如何設計互動模式，來促進使用者間的交流，並比較各平台的不同之處。 理解平台的互動機制後，接著探討平台的補貼準則。因為各網路交友平台的設計不同也使得補貼準則有所差異，透過文獻裡所述的補貼準則來分析平台是透過哪種方式來向使用者進行收費，以及分析使用者願意支付費用的原因。 透過幾個交友平台的個案分析，本研究觀察到雖都為網路交友平台，但是其交友的機制都會因其設計理念、交友目的而有所不同。因此本研究整理出哪些補貼準則被應用在網路交友平台上，而各交友平台如何設計收費時機在互動模式上，以理解網路交友平台的整個收費訂價的方式。 / Platform business model and online dating has become popular in recent years, therefore more and more online dating platforms are being set up. Platform pricing model is not set up by user charge alone, how users interact on the platform is also considered. Platform controller attract users who can cause positive cross-side network effect by offering them better price so that they can attract users who are willing to pay the fee. This research depends on two-side market theory to explain how online dating platforms attract users to enter their platforms, design interaction mechanism and set rules to allow users to use platforms easily. Depending on different dating purposes, every online dating platform has its own design. Therefore, this research discusses how different online dating platforms design interaction mechanism and compare the differences between them. After understanding how platforms design interaction mechanism, platform pricing model is then discussed. Every platform has its own pricing model, because of different design. This research analyzes platform pricing model by subsidy rules from previous studies, and why users are willing to pay. By analyzing several online dating platform cases, this research concludes that platforms have different interacting mechanisms because of website design purpose and user dating purpose. This research demonstrates which subsidy rules are used on online dating platform and how these platform design charge timing in order to understand online dating platform pricing model.

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The purpose of this research study was to conduct an exploration of the dating preferences of African American women and U.S. men between the ages of 30-74 years old. This research focuses on the dating preferences and desirability of African American women and if they are influential on the high unmarried rates of African American women. A weighted stratified sampling of 2,800 personal advertisements of African American, Asian, Latino and White men and women from Match.com were collected to conduct the research. The five research hypotheses of this study were tested using frequency and percentage distribution, logistic regression and cross-tabulation models. The findings partially support the hypotheses African American women are more likely to prefer a mate with a bachelor's degree or higher and African American women are more likely to prefer a mate of the same race compared to U.S. women of other races. The findings also suggested non-African American men are less likely to have an interest in dating African American women and non-African American men, who are interested in dating African American women, are less likely to prefer women with a bachelor's degree or higher or a more socially desirable body type.