Understanding the predictive power of social media

Kalampokis, Evangelos; Tambouris, Efthimios; Tarabanis, Konstantinos

doi:10.1108/intr-06-2012-0114

Cited by 149 publications

(114 citation statements)

References 60 publications

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“…Females have significantly higher frequency of "likes," comments and messages on Facebook than males do. The results verified that women have higher participation rates, higher frequency of posting and commenting to their friends 2,28,45 . This higher involvement made social support easier to exchange.…”

Section: Discussionsupporting

confidence: 65%

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Social Support on Facebook: The Influence of Tie Strength and Gender Differences

Luarn

Kuo

Chiu

et al. 2015

IJECS

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How do people define their online relationships? Do "friends" still offer social support to each other on Facebook? This article discusses the effects of tie strength and gender difference on social support for online friendships. The results showed that individuals with strong ties have a significantly higher frequency of clicking "like," and posting comments and messages on Facebook than individuals with weak ties do. In addition, females have a significantly higher frequency of liking, commenting and messaging than males. The results reconfirm the gender difference of social support in sociology and reveal the pattern behind user behavior on a social network website. These findings could be applied to the value proposition and to the design of interaction tools of social network websites in the future.

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Section: Discussionsupporting

confidence: 65%

“…Social network sites (SNSs) are changing the behavior of Internet users 1,2 . The appearance of SNSs has changed the form of information from centralization and broadcasting into collaboration and sharing 3 .…”

Section: Introductionmentioning

confidence: 99%

Social Support on Facebook: The Influence of Tie Strength and Gender Differences

Luarn

Kuo

Chiu

et al. 2015

IJECS

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“…At the time of searching, Academic Search Premier permitted export of 100 citations per batch and Web of Science permitted export of 500 citations per batch. All citations from each round of searches were exported in batches until all of the results were copied into EndNote online.Google Scholar was included as one of the databases searched for during this literature review due to its broad reach across interdisciplinary academic scholarship indexed on the Internet and its use in prior literature review studies (see Błachnio et al, 2013;Dhir et al, 2013;Kalampokis et al, 2013;Williams et al, 2013;Wilson et al, 2012). Unfortunately, Google Scholar has certain limitations.…”

mentioning

confidence: 99%

“…Some authors have focused on categorization of trends in academic literature related to specific social media platforms such as Facebook (Błachnio, Przepiórka, & Rudnicka, 2013;Caers et al, 2013;Hew, 2011;Manca & Ranieri, 2013;Nadkarni & Hofmann, 2012;Wilson, Gosling, & Graham, 2012), Twitter (Dhir, Buragga, & Boreqqah, 2013;Williams, Terras, & Warwick, 2013), or YouTube (Snelson, 2011). Other studies are grounded within a particular subject or field of study to examine social media as it relates to topics such as adolescent well-being (Best, Manktelow, & Taylor, 2014), health-care professionals (Hamm et al, 2013), type 1 diabetes (Jones, Sinclair, Holt, & Barnard, 2013), tourism and hospitality (Leung, Law, van Hoof, & Buhalis, 2013), or prediction of real-world events (Kalampokis, Tambouris, & Tarabanis, 2013).…”

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confidence: 99%

Qualitative and Mixed Methods Social Media Research

Snelson

2016

International Journal of Qualitative Methods

228

154

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Social media technologies have attracted substantial attention among many types of users including researchers who have published studies for several years. This article presents an overview of trends in qualitative and mixed methods social media research literature published from 2007 through 2013. A collection of 229 qualitative studies were identified through a systematic literature review process. A subset of 55 of these articles report studies involving a combination of qualitative and quantitative methods. Articles were reviewed, analyzed, and coded through a qualitative content analysis approach. Overall trends are presented with respect to the entire collection of articles followed by an analysis of mixed methods research approaches identified in the subset of 55 studies. The most commonly used research approaches involved collecting data from people through interview, focus group, and survey methodologies. Content analysis was the second most commonly used approach whereby researchers use Facebook posts, Tweets (Twitter posts), YouTube videos, or other social media content as a data source. Many of the studies involving combinations of quantitative and qualitative data followed a design resembling Creswell and Plano Clark's basic mixed methods typology (e.g., convergent parallel, explanatory sequential, and exploratory sequential).Keywords social media research, Web 2.0, Facebook, Twitter, YouTube, mixed methods, qualitative This article presents a descriptive methodological analysis of qualitative and mixed methods approaches for social media research. It is based on a systematic review of 229 qualitative or mixed methods research articles published from 2007 through 2013 where social media played a central role. Publication trends are presented for the entire set of articles followed by analysis of a subset of 55 studies that combined qualitative and quantitative approaches consistent with an established mixed methods typology (Creswell, 2014;Creswell & Plano Clark, 2011). The literature analysis is first contextualized by presenting a brief overview of related scholarly activity in the emerging field of social media research. This is followed by a discussion of publication trends and methodologies applied in this systematic literature review.Kaplan and Haenlein (2010) defined social media as '' . . . a group of Internet-based applications that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of User Generated Content'' (p. 61). The emergence of social media technologies has been embraced by a growing number of users who post text messages, pictures, and videos online (Duggan, 2013;Duggan, Ellison, Lampe, Lenhart, & Madden, 2015). Reports of worldwide social networking activity suggest that there were 1.96 billion users in 2015 with predictions of 2.44 billion users by 2018 (Statista, 2015). Of all the social networking sites, Facebook, Twitter, and YouTube are among the most popular ranking within the top 10 of a list of most heavily ...

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“…Social media data has been used as a primary source for the creation of predictive analytics models regarding various phenomena such as elections, stock market and product sales. An analysis of 52 relevant empirical studies concluded that social media data should go through a data conditioning process, which is similar to the one that we have presented in the proposed linked open government data analytics approach [19]. The same study revealed that this kind of open data could be successfully used for the development of predictive models in various problem areas.…”

Section: Related Workmentioning

confidence: 76%

Linked Open Government Data Analytics

Kalampokis

Tambouris

Tarabanis

2013

Lecture Notes in Computer Science

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Abstract. Although the recently launched Open Government Data (OGD) movement promised to provide a number of benefits, recent studies have shown that its full potential has not yet realized. The difficulty in exploiting open data seems surprising if we consider the huge importance data have in modern societies. In this paper we claim that the real value of OGD will unveil from performing data analytics on top of combined statistical datasets that were previously closed in disparate sources and can now be linked to provide unexpected and unexplored insights. To support this claim, we describe the linked OGD analytics concept along with its technical requirements and demonstrate its end-user value employing a use case related to UK general elections. The use case revealed that there is a significant relationship between the probability one of the two main political parties (i.e. Labour Party and Conservative Party) to win in a UK constituency and the unemployment rate in the same constituency.

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Understanding the predictive power of social media

Cited by 149 publications

References 60 publications

Social Support on Facebook: The Influence of Tie Strength and Gender Differences

Social Support on Facebook: The Influence of Tie Strength and Gender Differences

Qualitative and Mixed Methods Social Media Research

Linked Open Government Data Analytics

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