Instagram Pictures Research Articles

The dark side of #bodypositivity: The relationships between sexualized body-positive selfies on Instagram and acceptance of cosmetic surgery among women

One growing social media trend consists in posting body-positive content to subvert dominant feminine beauty ideals and help individuals to develop confidence and appreciation for their bodies. In spite of these goals, such posts, when sexualized, may promote an objectified representation of women's bodies resulting in a risk factor for body-related concerns. The present study aimed to investigate the links between viewing sexualized body-positive Instagram pictures and body image concerns among 493 young Italian women. They completed a self-reported questionnaire measuring the frequency of viewing sexually objectified body-positive selfies on Instagram, body surveillance, body satisfaction, and acceptance of cosmetic surgery. Results indicated that the frequency of viewing sexualized body-positive selfies was positively associated with body surveillance, which was negatively related to body satisfaction. In turn, body satisfaction was negatively associated with considering modifying one's body surgically and acceptance of cosmetic surgery for social reasons. Moreover, a serial mediation analysis showed that the frequency of viewing sexualized selfies was indirectly associated with higher acceptance of cosmetic surgery (considering having cosmetic surgery and social motivation for undergoing cosmetic surgery) via body surveillance and subsequent body satisfaction. Finally, study limitations and implications for future research on body-positive content on Instagram are discussed.

Visual content analysis of visitors’ engagement with an instagrammable exhibition

ABSTRACT This study aims to show how a museum exhibition designed to encourage visitors to take pictures can affect visitors’ behavior. We analyzed visitors’ engagement with the Yumi's Cell Special Exhibition (hereafter Yumi) held in South Korea, employing computer vision for the analysis of visitors’ Instagram pictures. Our research questions are: What types of pictures do visitors post on Instagram during or after their visit? And can Yumi’s instagrammable features make visitors interact more with the exhibition? We also formulated two corresponding hypotheses: Visitors are primarily interested in taking selfies in the instagrammable environment; and visitors struck more active poses when taking pictures in an instagrammable exhibition than in a traditional art exhibition. Through the image analysis of Instagram posts of the exhibition, we found many pictures of people, but the proportion of selfies was relatively limited. This suggests that visitors were more interested in interacting with the exhibition rather than taking selfies. This has also been confirmed by the pose analysis, which showed that the participatory feature of the exhibition encouraged visitors to take photos in active poses, interacting, mimicking, and performing. The framework presented and the findings offer insights about how to design exhibitions to increase visitors’ participation.

Measuring destination image: a novel approach based on visual data mining. A methodological proposal and an application to European islands

Availability of User Generated Content and the development of Big Data and machine learning algorithms have paved the way to collecting and analysing great volumes of data. We scan imagery data from traveling-related posts on Instagram to identify the key features of the destination image and of its dynamics. Specifically, we exploit a newly introduced Visual Object Recognition tool (Google Cloud Vision) to convert into textual labels the content of about 860,000 travel-related pictures posted on Instagram in Summer 2019 for several European islands. The output, a vector of labels’ frequencies on a very fine-grained scale, is used to proxy the destination image at different points in time. We then introduce the Index of Distance in Destination Image, a metric built on the pictures’ labels ranking, and aimed at providing a quantitative measure of (dis)similarity between destination images. We show that the analysis of labels and the index are fit to compare destinations cross-sectionally and over time, providing a useful tool for researchers, marketers and DMOs. We also deliver evidence on how external shocks (like extreme events linked to climate change) or the organization of events modify the cognitive sphere of the destination image, with repercussions on activities undertaken by tourists and relevant implications for local policies. • A Visual Object Recognition tool is applied to Instagram pictures posted by tourists. • The output is a vector of labels frequency for each destination and point in time. • An Index of Distance in Destination Images is proposed and applied to the output. • The metrics allows the investigation of differences and similarities across destinations. • Variation over time in destination image triggered by events is also found.

Color and engagement in touristic Instagram pictures: A machine learning approach

Color plays a critical role in recognizing tourist experiences and influencing their emotions. By classifying tourism photos on Instagram using machine learning, this study uncovers the relationship between color and user engagement based on pictures with different features. The findings show that the presence of the color blue in photos featuring natural scenery, high-end gastronomy, and sacral architectures contributes to user engagement. A red/orange color scheme enhances pictures regarding local delicacies and ambience, while the coexistence of violet and warm colors is crucial for photographs featuring cityscapes and interior design. By taking a broader lens from aesthetic philosophy and narrowing down to color psychology, this study offers guidelines for marketers to promote tourism activities through the application of color.

The Use of Computer Vision to Analyze Brand-Related User Generated Image Content

With the increasing popularity of visual-oriented social media platforms, the prevalence of visual brand-related User Generated Content (UGC) have increased. Monitoring such content is important as this visual brand-related UGC can have a large influence on a brand's image and hence provides useful opportunities to observe brand performance (e.g., monitoring trends and consumer segments). The current research discusses the application of computer vision for marketing practitioners and researchers and examines the usability of three different pre-trained ready-to-use computer vision models (i.e., YOLOV2, Google Cloud Vision, and Clarifai) to analyze visual brand-related UGC automatically. A 3-step approach was adopted in which 1) a database of 21,738 Instagram pictures related to 24 different brands was constructed, 2) the images were processed by the three different computer vision models, and 3) a label evaluation procedure was conducted with a sample of the labels (object names) outputted by the models. The results of the label evaluation procedure are quantitatively assessed and complemented with four concrete examples of how the output of computer vision can be used to analyze visual brand-related UGC. Results show that computer vision can yield various marketing insights. Moreover, we found that the three tested computer vision models differ in applicability. Google Cloud Vision is more accurate in object detection, whereas Clarifai provides more useful labels to interpret the portrayal of a brand. YOLOV2 did not prove to be useful to analyze visual brand-related UGC. Results and implications of the findings for marketers and marketing scholars will be discussed.

Self-Representations of Women’s Sport Fandom on Instagram at the 2015 FIFA Women’s World Cup

The purpose of this study is to investigate how fans of women’s sport are using Instagram to self-represent their fandom. It uses the 2015 FIFA Women’s World Cup (WWC) as a case study to examine the ways in which fans at a women’s sport event express their fandom through images and to consider the social and political dimensions of using Instagram for promoting women’s sport. Instagram pictures containing the event-related hashtags #FIFAWWC, #LiveYourGoals, #SheBelieves, and #CanadaRed were collected over the tournament duration. From a content analysis of 3,605 images, the authors argue that visual networked platforms are facilitating online communication conventions within sport fan communities that function as forms of social presence to legitimate women’s participation as fans and generate visibility for women’s sport. By demonstrating that the production and sharing of visual content related to sport events have become important features of the contemporary sport fan experience, this article advocates for greater recognition of social media practices alongside conventional measures of sport fan engagement.

The Battle of Social Media Platforms: The Use of Twitter, Youtube and Instagram in Corporate Communication

This study examines the usefulness of Twitter, YouTube and Instagram in corporate communication. We document that Twitter communication helps investors interpret earnings news and associates with stronger price reactions to earnings announcements. YouTube videos and Instagram pictures have either negative or no effect on investors’ ability to understand earnings information. Further, firms that post on the three social platforms experience positive price reactions to earnings announcements regardless of the news content, which suggests that investors perceive social media communication to signal higher disclosure effort. The effects we document dominate in stocks with high retail ownership and are robust to endogeneity bias. Our results suggest not all social media platforms help investors interpret earnings news, though social media communication plays an important signalling role.

Socio-spatial visualisations of cultural routes

Cultural routes, defined as routes of historical importance that geographically represent the shared and living cultural heritage of different countries, have recently gained attention both as tourist destinations and as social repositories of collective local memories. In this paper we argue that the recent development of digital humanities can open interesting new perspectives for the empirical exploration of these routes as cultural objects. Indeed, the availability of new digital traces generated by human activities and social media combined with tools that facilitate the exploration of such traces allow researchers to create new types of fieldwork online. In this paper, we present a case study focused on the Via Francigena cultural route. We added a geographical component to a graph analysis tool called histograph, making it possible to explore and analyse a corpus of more than 8,000 Instagram pictures. We investigate the potential of the prototype to uncover socio-spatial relations related to the itinerary and to hypothesise about the collective memories that the route conveys in this corpus.

INSTAGRAM USE TO ENHANCE ABILITY IN WRITING DESCRIPTIVE TEXTS

Technology is changing the world we live in. It affects the way people see, think, and learn their environment and communicate with others. In the educational field, there have been previous studies revealing the positive attitudes toward the use of mobile devices and applications. However, the empirical studies of the practice of how to use a specific mobile device and application effectively are done in a limited scale. Taking the experimental research method, this study investigated the effectiveness of the use of Instagram application on the students� performance in writing descriptive texts. The main research question was centred around whether there was significant difference in the ability of writing descriptive text between students who were taught using Instagram and those who aren�t. Involving random sampling technique, this study involved 50 students of a private high school in Yogyakarta as the research sample.� The empirical data were collected through pre and post tests. The data were analyzed quantitatively applying t-test computation and descriptive analysis. Results of the study indicate that there is significant difference in students writing score between those taught using Instagram and those who aren�t. In conclusion, teaching students writing by using Instagram pictures are more effective than teaching without using Instagram pictures. In other words, the use of Instagram is effective in teaching writing descriptive texts. �Keywords: technology; Instagram; experimental research; writing descriptive text.

Content Curators as Cultural Intermediaries: “My reputation as a curator is based on what I curate, right?”

Content Curators as Cultural Intermediaries: “My reputation as a curator is based on what I curate, right?”

Celebrating the power, promise of pharmacy at APhA’s Annual Meeting

Nearly 6,000 pharmacists and student pharmacists from every pharmacy practice setting converged in Orlando, FL, for the 2014 APhA Annual Meeting & Exposition on March 28 to 31. Attendees heard from thought leaders about changes and challenges facing the pharmacy profession, networked with colleagues, took in resources and information to strengthen their role as patient care providers, and celebrated the achievements of their peers. This year's theme, "The Power & Promise of Pharmacy," captured the changing role of pharmacists in health care.