Assessing the Value of Social Media for Organisations

Phethean, Christopher; Tiropanis, Thanassis; Harris, Lisa

doi:10.1145/2786451.2786457

Cited by 4 publications

(4 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the second stage of data collection, a series of interviews had been conducted with six informants who represent the campaign's audiences. To examine the form of activism and determine the value of social media use that the audience engaged in this campaign, we applied the framework of social media stages on awareness, engagement and action for developing the guideline questions (Phethean et al, 2015(Phethean et al, , 2013. The guideline questions were addressed to get a description of informant's understandings and engagements with Savesharks Indonesia campaign, which include these points: (1) What are their understandings about the campaign; (2) What type of engagement the informants involve in the campaign and what kind of messages that make them engaged (e.g.…”

Section: Methodsmentioning

confidence: 99%

Social Media, Youth and Environmental Low-Risk Activism: A Case Study of Savesharks Indonesia Campaign on Twitter

Hersinta

Sofia²

2022

aspiration

View full text Add to dashboard Cite

The lack of understanding and awareness on shark’s conservation in Indonesia is still largely found. Evidently, it could be seen from the massive reducing number of shark’s population, irresponsible consumption of shark meat, and constant activities on illegal, unregulated and unreported shark fishing and finning in Indonesia. On the other hand, shark existence is considered critical for sustainability in the marine area. In 2012, Savesharks Indonesia has started an online campaign on Twitter as their effort to raise public awareness of the critical role of sharks’ conservation. However, social media activism has the possibility to lead into ‘slacktivism’, or ‘feel good’ activism; without creating a meaningful impact for the cause. This article is intended to explore the relationship between online environmental activism and its implication toward the cause. On the first stage, we analyse the Twitter content in 2014 Savesharks campaign – based on Lovejoy & Saxton (2012) framework of communicative functions in Twitter environmental advocacy. On the second stage, we conduct interviews with informants who represent Savesharks’ campaign audience – to investigate the level of activism that the audience refers to in this campaign. Results indicate that Savesharks Indonesia online activism has reached the action stage where the audience were involved not only in online realm of activism but also in offline forms. However, the online activism of Savesharks Indonesia was reflecting more of a “populist political activism” (Lim, 2013). As such, it is still questionable whether the activism could lead to tangible political actions (e.g. influencing the environmental policies).

show abstract

Section: Methodsmentioning

confidence: 99%

Social Media, Youth and Environmental Low-Risk Activism: A Case Study of Savesharks Indonesia Campaign on Twitter

Hersinta

Sofia²

2022

aspiration

View full text Add to dashboard Cite

show abstract

“…Pollsters, politicians, and marketers alike have long histories of collating data from myriad sources to increase return on investment (ROI) (Malinen, 2015;Phethean et al, 2015;Schacht et al, 2015). More recently, citizen journalists and scientists are referencing across platforms as well (Starbird, Muzny, & Palen, 2012).…”

Section: Ethical Questions Regarding Cross-platform Data Collectionmentioning

confidence: 99%

“…marketing (Li & Duan, 2014;Phethean, Tiropanis, & Harris, 2015;Schacht, Hall, & Chorley, 2015), politics (Caton, Hall, & Weinhardt, 2015;Chung & Mustafaraj, 2011;Ratkiewicz et al, 2011), and bioinformatics (Bloom, Amber, Hu, & Kirsner, 2015;Jiang, 2017;Narimatsu, Sugawara, & Fukao, 2012;Tresp et al, 2016), pioneer applications for social media analyses to support better outcomes for individuals, commerce, and society. However, new technologies and permeability of the social media realms and real-life realms demand more accurate, more complete, and suitable research design.…”

mentioning

confidence: 99%

Editorial of the Special Issue on Following User Pathways: Key Contributions and Future Directions in Cross-Platform Social Media Research

Hall

Mazarakis

Chorley

et al. 2018

International Journal of Human–Computer Interaction

View full text Add to dashboard Cite

Social media and the resulting tidal wave of the available data have changed the ways and methods researchers analyze communities at scale. But the full potential for social scientists (and others) is not yet achieved. Despite the popularity of social media analysis in the past decade, few researchers invest in crossplatform analyses. This is a major oversight as a majority of online social media users have multiple social media accounts. Missing are the models and tools necessary to undertake analysis at scale across multiple platforms. Especially promising in support of cross-platform analysis is the mixed-method approach (e.g., qualitative and quantitative methods) in order to better understand how users and society interact online. This special issue "Following User Pathways" addresses methodological, analytical, conceptual, and technological challenges and opportunities of cross-platform analysis in social media ecosystems. Social media users traverse well-trodden paths across their preferred platforms, even as individual's breadth and depth may vary significantly. Research works concentrating on theories and applications of cross-platform social media are notably absent from the current discourse. This special issue continues the conversation of the "Following User Pathways" workshop introduced at association for computing machinery (ACM) factors in human-computer interaction in 2015 (Hall et al., 2016). In spite of the prevalence and availability of application programming interfaces (APIs) for data extraction, and an almost endless supply of papers and studies that focus on extraction and analysis of specific platforms, cross-platform analyses are lacking in the social media research domain. This is an oversight, in an age where over half of social media users have multiple social media profiles. 1 Chorley and Williams (2017) define social media as the set of applications having three characteristics: (1) The capability to support user-generated content. (2) The provision of a means for users to connect with one another. (3) Support for members to engage with one another. A deeper discussion on what exactly is "social media" can be found in McCay-Peet and Quan-Haase (2017) and Chorley and Williams (2017), as well as in Chorley and Williams (2017). This article discusses the merits and challenges of crossplatform analyses, and introduces four new studies in the cross-platform domain (

show abstract

“…This includes well-known networking sites, such as Facebook and Twitter, but also other platforms enabling users to interact with their content. Several domains evolved to take advantage of this overabundance of online activities, such as marketing [7,31,34] or cybersecurity [12,26]. These domains have an increasing interest in stance detection due to its wide range of applications.…”

Section: Introductionmentioning

confidence: 99%

Stance Classification through Proximity-based Community Detection

Fraisier

Cabanac

Pitarch

et al. 2018

Proceedings of the 29th on Hypertext and Social Media

View full text Add to dashboard Cite

Numerous domains have interests in studying the viewpoints expressed online, be it for marketing, cybersecurity, or research purposes with the rise of computational social sciences. Current stance detection models are usually grounded on the specificities of some social platforms. This rigidity is unfortunate since it does not allow the integration of the multitude of signals informing effective stance detection. We propose the SCSD model, or Sequential Community-based Stance Detection model, a semi-supervised ensemble algorithm which considers these signals by modeling them as a multi-layer graph representing proximities between profiles. We use a handful of seed profiles, for whom we know the stance, to classify the rest of the profiles by exploiting like-minded communities. These communities represent profiles close enough to assume they share a similar stance on a given subject. Using datasets from two different social platforms, containing two to five stances, we show that by combining several types of proximity we can achieve excellent results. Moreover, we compare the proximities to find those which convey useful information in term of stance detection.

show abstract

Assessing the Value of Social Media for Organisations

Cited by 4 publications

References 19 publications

Social Media, Youth and Environmental Low-Risk Activism: A Case Study of Savesharks Indonesia Campaign on Twitter

Social Media, Youth and Environmental Low-Risk Activism: A Case Study of Savesharks Indonesia Campaign on Twitter

Editorial of the Special Issue on Following User Pathways: Key Contributions and Future Directions in Cross-Platform Social Media Research

Stance Classification through Proximity-based Community Detection

Contact Info

Product

Resources

About