scholarly journals An Exploratory Perception Analysis of Consensual and Nonconsensual Image Sharing

Author(s):  
Jin Ree Lee ◽  
Steven Downing

Limited research has considered individual perceptions of moral distinctions between consensual and nonconsensual intimate image sharing, as well as decision making parameters around why others might engage in such behavior. The current study conducted a perception analysis using mixed-methods online surveys administered to 63 participants, inquiring into their perceptions of why individuals engage in certain behaviors surrounding the sending of intimate images from friends and partners. The study found that respondents favored the concepts of (1) sharing images with romantic partners over peers; (2) sharing non-intimate images over intimate images; and (3) sharing images with consent rather than without it. Furthermore, participants were more willing to use their own devices to show both intimate and non-intimate images rather than posting on social media or directly sending others the image files. Drawing on descriptive quantitative and thematic qualitative analysis, the findings suggest that respondents perceive nonconsensual image sharing as being motivated by the desire to either bully, “show off,” or for revenge. In addition, sharing intimate digital images of peers and romantic partners without consent was perceived to be troubling because it is abusive and/or can lead to abuse (when involving peers) and a violation of trust (when involving romantic partners).

2019 ◽  
Vol 21 (1) ◽  
pp. 26-32 ◽  
Author(s):  
Jeff Riddell ◽  
Alisha Brown ◽  
Lynne Robins ◽  
Rafae Nauman ◽  
Jeanette Yang ◽  
...  

Introduction: Twitter is growing in popularity and influence among emergency physicians (EP), with over 2200 self-identified EP users. As Twitter’s popularity has increased among EPs so too has its influence. While there has been debate about the value of Twitter as an effective educational delivery tool, little attention has been paid to the nature of the conversation occurring on Twitter. We aim to describe how influential EPs use Twitter by characterizing the language, purpose, frequencies, content, and degree of engagement of their tweets. Methods: We performed a mixed-methods analysis following a combined content analysis approach. We conducted qualitative and quantitative analyses of a sample of tweets from the 61 most influential EPs on Twitter. We present descriptive tweet characteristics and noteworthy themes. Results: We analyzed 1375 unique tweets from 57 unique users, representing 93% of the influential Twitter EPs. A majority of tweets (1104/1375, 80%) elicited some response in the form of retweets, likes, or replies, demonstrating community engagement. The qualitative analysis identified 15 distinct categories of tweets. Conclusion: Influential EPs on Twitter were engaged in largely medical conversations in which most messages generated some form of interaction. They shared resources and opinions while also building social rapport in a community of practice. This data can help EPs make informed decisions about social media engagement.


10.2196/19276 ◽  
2020 ◽  
Vol 6 (2) ◽  
pp. e19276 ◽  
Author(s):  
Abdullah Wahbeh ◽  
Tareq Nasralah ◽  
Mohammad Al-Ramahi ◽  
Omar El-Gayar

Background The coronavirus disease (COVID-19) pandemic is considered to be the most daunting public health challenge in decades. With no effective treatments and with time needed to develop a vaccine, alternative approaches are being used to control this pandemic. Objective The objective of this paper was to identify topics, opinions, and recommendations about the COVID-19 pandemic discussed by medical professionals on the Twitter social medial platform. Methods Using a mixed methods approach blending the capabilities of social media analytics and qualitative analysis, we analyzed COVID-19–related tweets posted by medical professionals and examined their content. We used qualitative analysis to explore the collected data to identify relevant tweets and uncover important concepts about the pandemic using qualitative coding. Unsupervised and supervised machine learning techniques and text analysis were used to identify topics and opinions. Results Data were collected from 119 medical professionals on Twitter about the coronavirus pandemic. A total of 10,096 English tweets were collected from the identified medical professionals between December 1, 2019 and April 1, 2020. We identified eight topics, namely actions and recommendations, fighting misinformation, information and knowledge, the health care system, symptoms and illness, immunity, testing, and infection and transmission. The tweets mainly focused on needed actions and recommendations (2827/10,096, 28%) to control the pandemic. Many tweets warned about misleading information (2019/10,096, 20%) that could lead to infection of more people with the virus. Other tweets discussed general knowledge and information (911/10,096, 9%) about the virus as well as concerns about the health care systems and workers (909/10,096, 9%). The remaining tweets discussed information about symptoms associated with COVID-19 (810/10,096, 8%), immunity (707/10,096, 7%), testing (605/10,096, 6%), and virus infection and transmission (503/10,096, 5%). Conclusions Our findings indicate that Twitter and social media platforms can help identify important and useful knowledge shared by medical professionals during a pandemic.


Author(s):  
Abdullah Wahbeh ◽  
Tareq Nasralah ◽  
Mohammad Al-Ramahi ◽  
Omar El-Gayar

BACKGROUND The coronavirus disease (COVID-19) pandemic is considered to be the most daunting public health challenge in decades. With no effective treatments and with time needed to develop a vaccine, alternative approaches are being used to control this pandemic. OBJECTIVE The objective of this paper was to identify topics, opinions, and recommendations about the COVID-19 pandemic discussed by medical professionals on the Twitter social medial platform. METHODS Using a mixed methods approach blending the capabilities of social media analytics and qualitative analysis, we analyzed COVID-19–related tweets posted by medical professionals and examined their content. We used qualitative analysis to explore the collected data to identify relevant tweets and uncover important concepts about the pandemic using qualitative coding. Unsupervised and supervised machine learning techniques and text analysis were used to identify topics and opinions. RESULTS Data were collected from 119 medical professionals on Twitter about the coronavirus pandemic. A total of 10,096 English tweets were collected from the identified medical professionals between December 1, 2019 and April 1, 2020. We identified eight topics, namely actions and recommendations, fighting misinformation, information and knowledge, the health care system, symptoms and illness, immunity, testing, and infection and transmission. The tweets mainly focused on needed actions and recommendations (2827/10,096, 28%) to control the pandemic. Many tweets warned about misleading information (2019/10,096, 20%) that could lead to infection of more people with the virus. Other tweets discussed general knowledge and information (911/10,096, 9%) about the virus as well as concerns about the health care systems and workers (909/10,096, 9%). The remaining tweets discussed information about symptoms associated with COVID-19 (810/10,096, 8%), immunity (707/10,096, 7%), testing (605/10,096, 6%), and virus infection and transmission (503/10,096, 5%). CONCLUSIONS Our findings indicate that Twitter and social media platforms can help identify important and useful knowledge shared by medical professionals during a pandemic.


CICES ◽  
2019 ◽  
Vol 5 (2) ◽  
pp. 188-203
Author(s):  
Ria Wulandari ◽  
M. Ifran Sanni ◽  
Dani Ramadhan

This research is motivated by a decline in motorcycle sales produced by PT. Yamaha Indonesia MFG in the 2014-2018 period. In this research there was a decrease in the decision on the power of interest in customer purchases on PT. Yamaha Indonesia MFG so that later can be analyzed in the formulation of this paper, that how customer take motorcycle purchase decisions amid the phenomenon of competition and increasingly crowded sales rivalries. The purpose of this research was to analyze the influence of motivation, perceived quality, and customer attitudes toward decisions in purchasing Yamaha motorbikes. This research uses quantitative and qualitative methods. The respondents in this research were 100 people who could meet one to five criteria consisting of; initiator (initiator), influencer (influencer), decision making (decider), purchase (buyer), user (user) motorcycle production PT. Yamaha Indonesia MFG. There are 3 hypotheses formulated and tested using the Regression Analysis method. In qualitative analysis it is obtained from the interpretation of processing data by providing information and explanation. In the results of this research shows the results of Motivation, Quality Perception, and Customer Attitudes have a relationship that has a significant impact on Purchasing Decisions.


2012 ◽  
Vol 3 (5) ◽  
pp. 379-381
Author(s):  
Dr. Aruna Kumar Mishra ◽  
◽  
Narendra Kumar Narendra Kumar ◽  
Abhishek Sharma

2020 ◽  
Vol 3 (2) ◽  
Author(s):  
Oktaria Ardika Putri

Instagram is a social media application that is currently very popular in the community, especially among artist, politicians, and business people. Companies or advanced business must quicly adapt to the advancement of information technology in the form of social media as a marketing tool. Instagram social media also necessary to developing educational institutions. One of the educational institution that ae currently developing is the newly established Faculty of Economics and Business Islam (FEBI) at the Kediri State Islamic Institute (IAIN Kediri). This writing aims to examine the importance of Instagram as social media marketing to building FEBI IAIN Kediri Brand Awareness. Instagram social media is considered more effectives to embrace students and the community, so it is expected to facilitate marketing and communication between FEBI IAIN Kediri with the students or other agencies. The method of this reasearch is a qualitative analysis which reference libraries are used as a basis. Keywods:  Instagam,  social media, Faculty of Economics and Business Islam, IAIN Kediri


2020 ◽  
Author(s):  
Lili Zhang ◽  
Himanshu Vashisht ◽  
Alekhya Nethra ◽  
Brian Slattery ◽  
Tomas Ward

BACKGROUND Chronic pain is a significant world-wide health problem. It has been reported that people with chronic pain experience decision-making impairments, but these findings have been based on conventional lab experiments to date. In such experiments researchers have extensive control of conditions and can more precisely eliminate potential confounds. In contrast, there is much less known regarding how chronic pain impacts decision-making captured via lab-in-the-field experiments. Although such settings can introduce more experimental uncertainty, it is believed that collecting data in more ecologically valid contexts can better characterize the real-world impact of chronic pain. OBJECTIVE We aim to quantify decision-making differences between chronic pain individuals and healthy controls in a lab-in-the-field environment through taking advantage of internet technologies and social media. METHODS A cross-sectional design with independent groups was employed. A convenience sample of 45 participants were recruited through social media - 20 participants who self-reported living with chronic pain, and 25 people with no pain or who were living with pain for less than 6 months acting as controls. All participants completed a self-report questionnaire assessing their pain experiences and a neuropsychological task measuring their decision-making, i.e. the Iowa Gambling Task (IGT) in their web browser at a time and location of their choice without supervision. RESULTS Standard behavioral analysis revealed no differences in learning strategies between the two groups although qualitative differences could be observed in learning curves. However, computational modelling revealed that individuals with chronic pain were quicker to update their behavior relative to healthy controls, which reflected their increased learning rate (95% HDI from 0.66 to 0.99) when fitted with the VPP model. This result was further validated and extended on the ORL model because higher differences (95% HDI from 0.16 to 0.47) between the reward and punishment learning rates were observed when fitted on this model, indicating that chronic pain individuals were more sensitive to rewards. It was also found that they were less persistent in their choices during the IGT compared to controls, a fact reflected by their decreased outcome perseverance (95% HDI from -4.38 to -0.21) when fitted using the ORL model. Moreover, correlation analysis revealed that the estimated parameters had predictive value for the self-reported pain experiences, suggesting that the altered cognitive parameters could be potential candidates for inclusion in chronic pain assessments. CONCLUSIONS We found that individuals with chronic pain were more driven by rewards and less consistent when making decisions in our lab-in-the-field experiment. In this case study, it was demonstrated that compared to standard statistical summaries of behavioral performance, computational approaches offered superior ability to resolve, understand and explain the differences in decision- making behavior in the context of chronic pain outside the lab.


2021 ◽  
Vol 13 (12) ◽  
pp. 6581
Author(s):  
Jooyoung Hwang ◽  
Anita Eves ◽  
Jason L. Stienmetz

Travellers have high standards and regard restaurants as important travel attributes. In the tourism and hospitality industry, the use of developed tools (e.g., smartphones and location-based tablets) has been popularised as a way for travellers to easily search for information and to book venues. Qualitative research using semi-structured interviews based on the face-to-face approach was adopted for this study to examine how consumers’ restaurant selection processes are performed with the utilisation of social media on smartphones. Then, thematic analysis was adopted. The findings of this research show that the adoption of social media on smartphones is positively related with consumers’ gratification. More specifically, when consumers regard that process, content and social gratification are satisfied, their intention to adopt social media is fulfilled. It is suggested by this study that consumers’ restaurant decision-making process needs to be understood, as each stage of the decision-making process is not independent; all the stages of the restaurant selection process are organically connected and influence one another.


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