CRM in social media: Predicting increases in Facebook usage frequency

Ballings, Michel; Poel, Dirk Van den

doi:10.1016/j.ejor.2015.01.001

Cited by 62 publications

(49 citation statements)

References 80 publications

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“…There are three large clusters in the network. In the first, largest cluster ( N = 74), several papers sought to predict the risk of credit applicants (Abellán and Castellano, ; Florez‐Lopez and Ramon‐Jeronimo, ; Twala, ; Wang et al ., ), others predicted customer churn/retention risks (Ballings and Poel, ; Moeyersoms and Martens, ; Morales and Wang, ), whereas more niche topics are also included, for instance, social media usage predictions (Ballings and Van den Poel, ). Papers in the second cluster ( N = 56) examined what organizational characteristics affect firm performance in the era of BDA (Akter et al ., ; Ji‐fan Ren et al ., ; Wamba et al ., ) and how BDA improved decision‐making and value creation in organizations (Cao, Duan and Li, ; Chae, Olson and Sheu, ; Chae et al ., ; Chen, Preston and Swink, ; Coltman, Devinney and Midgley, ).…”

Section: Resultsmentioning

confidence: 97%

History, Evolution and Future of Big Data and Analytics: A Bibliometric Analysis of Its Relationship to Performance in Organizations

Batistič

Laken

2019

British J of Management

134

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Big data and analytics (BDA) are gaining momentum, particularly in the practitioner world. Research linking BDA to improved organizational performance seems scarce and widely dispersed though, with the majority focused on specific domains and/or macro‐level relationships. In order to synthesize past research and advance knowledge of the potential organizational value of BDA, the authors obtained a data set of 327 primary studies and 1252 secondary cited papers. This paper reviews this body of research, using three bibliometric methods. First, it elucidates its intellectual foundations via co‐citation analysis. Second, it visualizes the historical evolution of BDA and performance research and its substreams through algorithmic historiography. Third, it provides insights into the field's potential evolution via bibliographic coupling. The results reveal that the academic attention for the BDA–performance link has been increasing rapidly. The study uncovered ten research clusters that form the field's foundation. While research seems to have evolved following two main, isolated streams, the past decade has witnessed more cross‐disciplinary collaborations. Moreover, the study identified several research topics undergoing focused development, including financial and customer risk management, text mining and evolutionary algorithms. The review concludes with a discussion of the implications for different functional management domains and the gaps for both research and practice.

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Section: Resultsmentioning

confidence: 97%

History, Evolution and Future of Big Data and Analytics: A Bibliometric Analysis of Its Relationship to Performance in Organizations

Batistič

Laken

2019

British J of Management

134

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“…Previous research has shown that including Facebook data contains many valuable variables and can lead to accurate recommendations (Kalampokis et al 2013). For example, Ballings and Van den Poel (2015a) revealed that accurate predictions can be achieved for Facebook usage frequency using a wide variety of user-related variables. Bogaert et al (2016a) went one step further and showed that the inclusion of Facebook friends is beneficial in event prediction.…”

Section: Literature Overviewmentioning

confidence: 99%

“…Hence, in our case, we calculated the accuracy after dichotomizing the propensity scores using a threshold that results in the top 10% of users being assigned a 1 and the remaining users being a 0. This model evaluation corresponds to the real-life situation in which 10% of the users will be targeted (Ballings and Van den Poel 2015a).…”

Section: Performance Evaluationmentioning

confidence: 99%

“…Before the existence of social media, companies had to rely on expensive commercial databases to implement targeted marketing strategy companies (D'Haen et al 2016). However, the Internet and social media offer an inexpensive and effective alternative (Ballings and Van den Poel 2015a). In that regard, Facebook can be considered as the most important social media channel given that (1) it has 1.79 billion monthly active users (Facebook 2017) and (2) it contains a large number of variables related to customer engagement (e.g., likes and comments) (Malthouse et al 2013).…”

Section: Introductionmentioning

confidence: 99%

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Identifying Soccer Players on Facebook Through Predictive Analytics

Bogaert¹,

Ballings²,

Hosten³

et al. 2017

Decision Analysis

Self Cite

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Abstract. This study assesses the feasibility of identifying self-reported sports practitioners (soccer players) on Facebook. The main goal is to develop a system to support marketers with the decision as to which prospects to target for advertising purposes. To do so, we benchmark several algorithms (i.e., random forest, logistic regression, adaboost, rotation forest, neural networks, and kernel factory) using five times twofold cross-validation. To evaluate performance and variable importances, we build a fusion model, which combines the results of the other algorithms using the weighted average. This technique is also referred to as information-fusion sensitivity analysis. The results reveal that Facebook data provide a viable basis to come up with sports predictions as the predictive performance ranges from 72.01% to 80.43% for area under the receiver operating characteristic curve (AUC), from 81.96% to 83.95% for accuracy, and from 2.41 to 3.06 for top-decile lift. Our benchmark study indicates that stochastic adaboost, the fusion model, random forest, rotation forest, and regularized logistic regression are the best-performing algorithms. Furthermore, the results show that the most important variables are the average number of friends that play soccer, membership of a soccer group, and the number of favorite teams. We also assess the impact of our results on profitability by conducting a thorough sensitivity analysis. Our analysis reveals that our approach can be beneficial for a wide range of companies. The analysis and results in this study will assist sports brands with decisions regarding their implementation of targeted marketing approaches.

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“…Shared media use for shared change can be well-off. In support of e-destinations the preeminent practices are acknowledged through the facilitate of a total theme study of vocations' web link showing up and weblog relevances plus height of implementation of technologies and applications (Ballings and Van den Poel, 2015). So far e-destination and social media branding of Nepalese destinations is concerned, a painstaking data of tourism in Nepal by the world travel and tourism council are stated in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

Super-connected: How Techno Tourism Redesigns Our Lives Through Meaningful Travel

Karna¹,

Ye²,

Karn³

2017

Proceedings of the International Conference on Transformations and Innovations in Management

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The techno-tourism life brings together insights about innovative tourism and examines how travel life is influenced when social network structure like "Facebook" enters the picture. The end result is a landmark analysis of digital socialization and the knock of the internet and digital media across travel institutions. This research circumscribes the 'tourists-marketers facebook pages' of Nepal. Using archived online narratives from facebook page of travel-marketers (TMs), after the event of Nepal earthquake 2015, this study seeks to examine how techno-tourism redesigns lives through meaningful travel plus the coverage toward which event enthusiasts participate in chats of interactional causes. This study first of all dissects the intrinsic features of the facebook just like facebook pages exploitation by travel marketers during Nepal's earthquake disaster at district, zonal and state level. The study then offers some interesting insights for tourism marketers. It involves the statistical and mathematical model to observational and experimental datasets of their facebook posts and fans participation. This research drafts the importance of network science of super-connected digital voyagers, studying their sways, their point of views, their approaches of travel and their intensions for inspiring this style of travel feasible in requisites of work and money. As relationships are the foundation for social media sites; facebook is primarily used to raise awareness and create story telling. Hence this investigative study also has meaningful implications for public policy as well as super-connection as global impact. By adducing human race into one another's care, letting them to fathom commonalities, likewise endowing the resources by which they can super-connect one another, the digital media and World Wide Web chip-in greatly to the "techno-social life". This research is a great choice for general readers interested in this topic as well.

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CRM in social media: Predicting increases in Facebook usage frequency

Cited by 62 publications

References 80 publications

History, Evolution and Future of Big Data and Analytics: A Bibliometric Analysis of Its Relationship to Performance in Organizations

History, Evolution and Future of Big Data and Analytics: A Bibliometric Analysis of Its Relationship to Performance in Organizations

Identifying Soccer Players on Facebook Through Predictive Analytics

Super-connected: How Techno Tourism Redesigns Our Lives Through Meaningful Travel

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