Emotion and sentiment in social and expressive media: Introduction to the special issue

Rosso, Paolo; Bosco, Cristina; Damiano, Rossana; Patti, Viviana; Wang, Zhaoxia

doi:10.1016/j.ipm.2015.11.002

Cited by 11 publications

(4 citation statements)

References 17 publications

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“…Instant information sharing is often emotionally oriented (Choi & Toma, 2014;Rosso et al, 2016;Stieglitz & Dang-Xuan, 2013). It has been highlighted that emotions act as crucial determinants in successful and effective communication in social interactions (Cambria, 2016).…”

Section: The Effect Of Positive Emotion On the Urge To Share Informationmentioning

confidence: 99%

“…As mentioned previously, instant information sharing in social media tends to be conducted with limited cognitive capacity (Wang et al, 2015). The lack of cognitive evaluation and disregard for the consequences of communication readily induce individuals to be controlled by affective cues, rather than the reflective decision making process (Rosso et al, 2016;Strack et al, 2006). Importantly, it should be noted that the influence of affective dimensions (i.e., feelings and emotions) emerges not only in personal engagement (Celli et al, 2016;Rangel & Rosso, 2016) but also in crowdsourced content (Aljanaki et al, 2016;Tobias, 2011).…”

Section: The Influence Of Affective Cues On Positive Emotionmentioning

confidence: 99%

“…There is then a continuous loop of interaction between users and the social media environment that generates spontaneous, unstructured, and multi-faceted user responses (Rosso et al, 2016). Moreover, information sharing on microblogs always conveys individuals' emotional state and the intended emotional communication (Bollen et al, 2011), which might trigger a high level of arousal and information diffusion (Stieglitz & Dang-Xuan, 2013).…”

Section: Introductionmentioning

confidence: 99%

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The influence of affective cues on positive emotion in predicting instant information sharing on microblogs: Gender as a moderator

Wang

Zhou

Jin

et al. 2017

Information Processing & Management

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Instant information sharing on microblogs is important for promoting social awareness, influencing customer attitudes, and providing political and economic benefits. However, research on the antecedents and mechanisms of such instant information sharing is limited. To address that issue, this study develops a research model to investigate the factors (affective cues in particular) that drive users to instantly share information on microblogs and explores the moderating role of gender. An online survey was conducted on a microblogging platform to collect data for testing the proposed research model and hypotheses. The results confirm the positive effects of informational (i.e., information uniqueness), ambient (i.e., information crowding), and social (i.e., social interactivity) cues on individuals' positive emotion, which subsequently promotes their urge to share information on microblogs. Moreover, the moderating effects of gender are identified. This study contributes to the understanding of instant information sharing from an impulsive behavior perspective. The results also provide important insights for service providers and practitioners who wish to promote instant information sharing on microblogs.

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Section: The Effect Of Positive Emotion On the Urge To Share Informationmentioning

confidence: 99%

Section: The Influence Of Affective Cues On Positive Emotionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The influence of affective cues on positive emotion in predicting instant information sharing on microblogs: Gender as a moderator

Wang

Zhou

Jin

et al. 2017

Information Processing & Management

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“…Related tasks include personality prediction [22,21], interests identification [20,34] (a.k.a. genres), sentiment and emotion recognition [37], among others. Generally speaking, AP has been approached as a single-label classification problem, where the target profiles (e.g., males vs. females) stand for the target classes.…”

Section: Related Workmentioning

confidence: 99%

A visual approach for age and gender identification on Twitter

Álvarez‐Carmona

Pellegrin

Montes-y-Gómez

et al. 2018

IFS

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The goal of Author Profiling (AP) is to identify demographic aspects (e.g., age, gender) from a given set of authors by analyzing their written texts. Recently, the AP task has gained interest in many problems related to computer forensics, psychology, marketing, but specially in those related with social media exploitation. As known, social media data is shared through a wide range of modalities (e.g., text, images and audio), representing valuable information to be exploited for extracting valuable insights from users. Nevertheless, most of the current work in AP using social media data has been devoted to analyze textual information only, and there are very few works that have started exploring the gender identification using visual information. Contrastingly, this paper focuses in exploiting the visual modality to perform both age and gender identification in social media, specifically in Twitter. Our goal is to evaluate the pertinence of using visual information in solving the AP task. Accordingly, we have extended the Twitter corpus from PAN 2014, incorporating posted images from all the users, making a distinction between tweeted and retweeted images. Performed experiments provide interesting evidence on the usefulness of visual information in comparison with traditional textual representations for the AP task.

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Dissecting emotion and user influence in social media communities: An interaction modeling approach

Chung

Zeng

2020

Information & Management

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Emotion and sentiment in social and expressive media: Introduction to the special issue

Cited by 11 publications

References 17 publications

The influence of affective cues on positive emotion in predicting instant information sharing on microblogs: Gender as a moderator

The influence of affective cues on positive emotion in predicting instant information sharing on microblogs: Gender as a moderator

A visual approach for age and gender identification on Twitter

Dissecting emotion and user influence in social media communities: An interaction modeling approach

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