“…Emotion is one of the most important drivers for online audience. Videos, evoking strong and mostly positive emotions, are more likely to be shared within online communities [84]. Similarly, content that generates high-arousal emotions (e.g., awe, anxiety) disseminates faster on the Internet and captures a larger amount of users' interest [85,86].…”
Section: What Makes Web Content Popular?mentioning
Social media platforms have democratized the process of web content creation allowing mere consumers to become creators and distributors of content. But this has also contributed to an explosive growth of information and has intensified the online competition for users attention, since only a small number of items become popular while the rest remain unknown. Understanding what makes one item more popular than another, observing its popularity dynamics, and being able to predict its popularity has thus attracted a lot of interest in the past few years. Predicting the popularity of web content is useful in many areas such as network dimensioning (e.g., caching and replication), online marketing (e.g., recommendation systems and media advertising), or real-world outcome prediction (e.g., economical trends). In this survey, we review the current findings on web content popularity prediction. We describe the different popularity prediction models, present the features that have shown good predictive capabilities, and reveal factors known to influence web content popularity.
“…Emotion is one of the most important drivers for online audience. Videos, evoking strong and mostly positive emotions, are more likely to be shared within online communities [84]. Similarly, content that generates high-arousal emotions (e.g., awe, anxiety) disseminates faster on the Internet and captures a larger amount of users' interest [85,86].…”
Section: What Makes Web Content Popular?mentioning
Social media platforms have democratized the process of web content creation allowing mere consumers to become creators and distributors of content. But this has also contributed to an explosive growth of information and has intensified the online competition for users attention, since only a small number of items become popular while the rest remain unknown. Understanding what makes one item more popular than another, observing its popularity dynamics, and being able to predict its popularity has thus attracted a lot of interest in the past few years. Predicting the popularity of web content is useful in many areas such as network dimensioning (e.g., caching and replication), online marketing (e.g., recommendation systems and media advertising), or real-world outcome prediction (e.g., economical trends). In this survey, we review the current findings on web content popularity prediction. We describe the different popularity prediction models, present the features that have shown good predictive capabilities, and reveal factors known to influence web content popularity.
“…Images were downloaded from websites obtained through the google image search results. Given that all images were found online, we consider our RACIAL MICROAGGRESSIONS AND PERCEPTIONS OF INTERNET MEMES 14 stimuli to be Internet memes (see Guadagno et al, 2013). Because People of Color report experiencing online racial discrimination to a greater extent than their White counterparts (Pew Research Center, 2014;Tynes et al, 2013), we were primarily interested in comparing perceptions of biases memes where a racial minority was the target of discrimination to perceptions of non-biased memes.…”
Section: Racial Themed Internet Memesmentioning
confidence: 99%
“…Internet memes are a popular and pervasive phenomenon (Bauckhage, Kersting, & Hadiji, 2013) that may contribute to the climate of racial discrimination that can exist in online communities (Dyer-Barr, 2010;Tynes, Giang, Williams, & Thompson, 2008;Tynes & Markoe, 2010). Internet memes are individual bits of cultural information, such as an image with a caption, that are widely shared electronically (Guadagno, Rempala, Murphy, & Okdie, 2013). Although Internet memes are often intended to be humorous social commentaries (Davison, 2012;Knobel & Lankshear, 2007), they can be racist in nature (Davison, 2012;Milner, 2013).…”
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RACIAL MICROAGGRESSIONS AND PERCEPTIONS OF INTERNET MEMES 2
AbstractAlthough more blatant forms of discrimination have declined, racial prejudice continues to manifest itself in subtle ways. For example, People of Color experience racial microaggressions (i.e., subtle slights or 'put downs') in their face-to-face interactions (Nadal, 2011) and in online contexts (Clark et al., 2011). This study investigates whether experiencing subtle racial discrimination offline can influence perceptions of online content, specifically racial themed Internet memes. Results indicate that although both People of Color and Whites viewed racial themed memes to be more offensive than non-racial themed memes (control images), for People of Color the ratings of racial themed memes were predicted by previous discrimination; those who reported experiencing more racial microaggressions in everyday settings rated racial themed memes as more offensive. The same pattern of results did not emerge for ratings of non-racial themed memes or for White participants. These results provide initial evidence that experiencing racial microaggressions in offline interactions may lead individuals from racial minority groups to be more likely to perceive racial discrimination in online settings.Word Count: 169/200
“…The women's emotional links with the stories are generally positive, which contributes to converting their comments into a rite to kindness and friendship, which is a particularly relevant characteristic considering that the role of the Internet facilitates the spread of emotions (Guadagno et al, 2013(Guadagno et al, , p. 2318. The absence of denigrating expressions, controversies or disputes, is reflected in the repeated use of emoticons and other strategies destined to emphasise comments, such as exclamation marks and capital letters (Bury, 2005).…”
The construction of online gender identities around television fiction has been dominated by studies on eminently masculine cult fandoms. This article attempts to overcome this through the specific examination of the construction of online identities of women on social networks and forums dedicated to Spanish television fiction. The methodology employed combines manual techniques (gathering the comments) and computational processes (ATLAS.ti). The results of the analysis reveal that unlike cult fandoms, the female participants of our study do not seek to claim an identity. Instead, they reveal their desire to express and share sentiments and emotions generated through the interrelationship between the programmes and their daily lives. Female cultural identities are not used politically or as a claim.Keywords: Online communication, gender identity, social audience, TV fiction, fandom.
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RESUMENLa construcción de identidades de género online en torno a la ficción televisiva ha estado dominada por las investigaciones sobre los cult fandom, que son eminentemente masculinos. El artículo intenta superar este punto de vista mediante el examen específico de la construcción identitaria online de las mujeres en las redes sociales y los foros dedicados a la ficción televisiva española. La metodología implementada combina técnicas manuales (recogida de los comentarios) y computacionales (ATLAS.ti). Los resultados del análisis revelan que, a diferencia de los cult fandom, las participantes de nuestro estudio no buscan la reivindicación identitaria, sino que en todo caso muestran su voluntad de expresar y compartir sentimientos y emociones suscitados por la interrelación entre los programas y su vida cotidiana. Tampoco se hace un uso político ni reivindicativo de las identidades culturales femeninas.Palabras clave: comunicación online, identidad de género, audiencia social, ficción TV, fandom.
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