HOW DO CONSUMERS USE SOCIAL SHOPPING WEBSITES? THE IMPACT OF SOCIAL ENDORSEMENTS

Social endorsements are user-generated endorsements of products or services, such as “likes” and personal collections, in an online social platform. We examine the effect of prior social endorsements on subsequent users’ tendency to endorse or examine a product in a social shopping context, where a social platform connect consumers and enable a collaborative shopping experience. This research consists of two parts. In part I, we identify two ways prior social endorsements can affect subsequent user behavior: as a crowd endorsement, which is an aggregate number of endorsements a product receives for anyone who comes across the product, and as a friend endorsement, which is an endorsement with the endorser’s identity delivered only to the endorser’s friends or followers. Using a panel data of 1656 products on a leading social shopping platform, we quantify the relationship between crowd and friend endorsements and subsequent examination (“click”) and endorsement (“like”) of the products, noting that examination is a private behavior while endorsement is a public behavior. Our results are consistent with the identity signaling theory where identity-conscious consumers converge with the aspiration group (the followers) in their public behavior (e.g. endorsement) and diverge from the avoidance groups (the crowd). We also find differences between public and private behaviors. Moreover, the symbolic nature of social shopping platform trumps the traditional dichotomy of symbolic/functional product attributes. Part II of this study seeks to clarify the underlying mechanism through lab experiments. We hypothesize that consumers’ evaluative attitude, specifically the value-expressive type, moderates the relationship between crowd and friend endorsements and a focal user’s product choice. Our initial results of the second study show support for this idea in the cases when the product choice is not obvious

Nostalgia and iPhone Camera Apps: An Ethnographic Visual Approach to iPhoneography

The iPhone is the most popular smartphone and camera on social media. iPhoneography, the photography taken or edited with the iPhone, has set the trend of nostalgic photography on social media during the 2010s; thus, the iPhone, a high-tech camera, produces low-tech-looking images. This dissertation attempts to find out why iPhone photographers (iPhoneographers) take, edit, and share images that mimic photographs taken with analog photographic equipment. I argue that nostalgia allows iPhoneographers to use the iPhone as a creative tool and to belong to a community. Based on the arguments of Vilém Flusser—who suggested that photographers are more interested in the camera and the process of taking pictures than in the photographs produced—this work focuses first on the iPhone camera and the camera apps. (This work also considers the writings of Roland Barthes, Susan Sontag, and W. J. T. Mitchell, as they pertain to photography and iPhoneography.) It traces the beginning of the nostalgic photograph style to 2008, when the Apple App Store offered apps that behaved like toy cameras and rendered images similar to those produced by toy and Polaroid cameras. The Hipstamatic app set the trend in 2009, and Instagram made it mainstream. Nostalgia is more a source of inspiration and creativity than a source of melancholy and longing for the past. The iPhoneography community on Facebook tends to form small groups that share and curate specific topics, such as clouds, portraits, flowers, and images produced with Hipstamatic. A small survey of the iPhoneography community shows that the community considers iPhoneography an art

Potential Parallels Between Pro-Ana and Bodybuilding Content on Social Media

This thesis examined the relationship between pro-ana and bodybuilding social media content to understand the similarities between these populations’ identities and help inform social media content policies. Two interrelated studies were used to investigate this relationship: Study 1 used computational methods which compared the content through machine classification of pro-ana and bodybuilding social media posts on Twitter and Study 2 fielded an online survey experiment to compare the perceptions and human classification of content from these populations on Instagram. The findings from both studies broadly revealed that pro-ana and bodybuilding identities are similar, at least in social media content, which raises concern for the current state of social media censorship policies. The results of this thesis highlight the critical need for social media censorship policies to be cognizant of different populations expressing the same content, creating discrepancies when only one is censored

Identification & Role of Implicit Social Ties from Social Data

The concept of social ties was introduced by Granovetter through the seminal paper titled" Strength of weak ties". Across the past five decades, this topic has attracted much attention from both academics and practitioners. In the past two decades, the rapid increase in digitization and new modes of communication have led to collecting and analyzing data about people. One of the most popular sources for such large and granular data about people is social media platforms. The rise in the popularity of social media in the past 15 years has resulted in many research studies that have used social media data to understand a lot of different phenomena. Some of this research has focused on using social data, including social media data, on identifying different kinds of social ties online and the role these social ties play in various contexts. Over the past decade, many different approaches and models have been built to identify social ties using social media data. These methods have been built using private data and explicit social relationship data of users’ social media platforms. However, in the past few years, it has become nearly impossible to access this kind of social media data due to the changes in the business models of the social media platforms and the introduction of new privacy laws like GDPR. This thesis aims to identify the social ties from publicly available social data and study the role of the identified social ties in different contexts like business conferences and business phenomena. In order to achieve this research objective, three separate studies were conducted. The first two studies were single-case case studies, while the third was an experiment where two different sets of hypotheses were tested using empirical data. All three studies used publicly available social media data related to a specific context. The first study used a large dataset related to a game developer community on Facebook. The second study used social media data related to a business event from Twitter and Facebook. The third study used a large dataset associated with social media data about crowdfunding projects from Twitter. This study adds to the existing literature related to identifying social ties from social media data in multiple manners. The thesis illustrates a novel approach based on reciprocal interaction for filtering relevant social ties from large publicly available social media data. The thesis also contributes to the understanding of the role multiple social media platforms play in an event. Thus, showing the impact this can have on identifying social ties from publicly available social media data in case of an event. The dissertation adds to the existing literature about the role social ties have towards crowdfunding success. The thesis shows that implicit social ties, in general, positively impact crowdfunding project success. In addition, the thesis has practical implications for designers of conference recommendation systems. The dissertation also has implications for the crowdfunding project owners and the crowdfunding project campaign designers

Information of social media platforms: the case of Last.fm

Social media has become a global phenomenon. Currently, there are 2 billion active users on Facebook. However, much of the research on social media is about the consumption side of social media rather than the production or operational aspects of social media. Although research on the production side is still relatively small, it is growing, indicating that it is a fruitful area to study. This thesis attempts to contribute to this area of research to unravel the inner operations of social media with one key research question: How does social media platform organize information? The theory of digital object of Kallinikos et al. (2013) is used to investigate this question. Information display that users of a social media platform interact with is a digital object and it is constructed by two key components which are a database and algorithms. The database and the algorithms shape how information is being organized on information displays, and these influence user behaviors which are then captured as social data in the database. This thesis also critically examines the technology of recommender system by importing engineering literature on information filtering and retrieval. While newsfeed algorithm such as EdgeRank of Facebook has already been critically examined, information systems and media scholars have yet to investigate recommendation algorithms, despite the fact that they have been widely deployed all over the Internet. It is found that the key weakness of recommendation algorithms is their inability to recommend novel items. This is because the main tenet of any recommender system is to “recommend similar items to those that users already like”. Fortunately, this problem can be alleviated when recommender system is being deployed in the digital information environment of social media platforms. In turn, seven theoretical conjectures can be postulated. These are (1) navigation of information display as assembled by social media is highly interactive, (2) information organization of social media is highly unstable which would also render user behaviors unstable, (3) quality of data aggregation casts significant implications on user behaviors, (4) the amount of data captured by social media platforms limits the usefulness of their information displays, (5) output from the recommendation algorithm (recommendation list) casts real implications on user behaviors, (6) circle of friends on a social network can influence user behaviors, and (7) metadata attached to items being displayed casts influence on user behaviors. Data from Last.fm, a social media for music discovery, is used to evaluate these conjectures. The analysis supported most of the conjectures except the instability of information display and the importance of metadata attached to items being displayed. Some kinds of information organization are more stable than initially expected and some kinds of user generated contents are not so important for user behaviors

Selfies On Social Media: The Role Of Appearance Contingent Self-Worth And Impact On Self-Esteem

In this dissertation, women’s motivation to post selfies, defined as self-taken photographs of only themselves, and the impact of feedback received on these images on self-esteem was investigated. It was hypothesized that women higher in appearance contingent self-worth would have a stronger desire for positive appearance feedback, and that this would result in more frequent selfie posting, as this could be a means of soliciting positive feedback. In addition, it was hypothesized that women higher in appearance contingent self-worth would be more strongly impacted by feedback received on selfies than would women lower in appearance contingent self-worth given that this feedback could be perceived as being appearance-based. Three studies were conducted online, all with female undergraduate students. In Study I (N = 297), survey-based data were collected, and the results indicated that although the correlation between appearance-contingent self-worth and frequency of selfie posting was not significant, there was a significant indirect relationship through the desire to obtain positive appearance feedback. Further, exploratory analyses revealed that appearance contingent self-worth was both directly and indirectly related to the extent to which women edit their photos. In Study II (N = 48), women’s Instagram accounts were accessed to obtain information about the average proportion of their followers who liked their selfies and provided positive appearance-based comments over two months. This information was used in conjunction with self-report measures to determine whether the amount of feedback received was associated with women’s trait self-esteem and appearance satisfaction over that time period. However, due to difficulties with recruitment, all analyses were underpowered and limited conclusions could be drawn about the relationships between selfie feedback on one hand and trait self-esteem and appearance satisfaction on the other. Lastly, in Study III (N = 175), an experimental design was used to determine whether receiving more or less likes than expected on a posted selfie affected women’s state appearance and social self-esteem and resulted in changes in women’s global state self-esteem. The results indicated that receiving more or less likes than expected on a selfie affected changes in global self-esteem, such that women who received more likes than expected experienced increases in state global self-esteem. Appearance contingent self-worth was assessed as a moderator of these potential effects, but was not significant. However, appearance contingent self-worth affected the interpretation of women’s number of received likes. Women higher in appearance contingent self-worth were more likely to attribute their number of received likes to their appearance than were women lower in appearance contingent self-worth. Taken together, the findings of this research suggest that although women higher in appearance contingent self-worth may have a stronger desire for appearance feedback and therefore post selfies more frequently, selfie posting may not always be an appearance-driven act. Appearance contingent self-worth was not directly related to selfie posting, nor did it moderate the impact of received likes on self-esteem. Further, research on the uses and gratifications associated with posting selfies on social media indicates that posting selfies to show one’s appearance and/or gain self-confidence is only one potential motivator underlying the posting of these photos (Alblooshi, 2015; Sung et al., 2016)