Identifying reputation collectors in community question answering (CQA) sites: Exploring the dark side of social media

Roy, Pradeep Kumar; Singh, Jyoti; Baabdullah, Abdullah M.; Kizgin, Hatice; Rana, Nripendra P.

doi:10.1016/j.ijinfomgt.2018.05.003

Cited by 32 publications

(20 citation statements)

References 57 publications

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“…In an age where social media and word of mouth dominate the cyber world (Dwivedi et al, 2018;Kapoor et al, 2018;Roy et al, 2018), the effects of social relationships can either maintain or increase the usage of a given technological service or divert users towards a socially acceptable new technology (Al-Somali et al, 2009;Williams et al, 2015). Indeed, users might switch their usage of non-socially acceptable technology to socially acceptable technology in order to get higher levels of social interaction and integration (Jahya, 2004).…”

Section: Social Influence (Si)mentioning

confidence: 99%

Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model

Baabdullah

Alalwan

Rana

et al. 2019

International Journal of Information Management

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407

286

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Mobile banking is one of the most promising technologies that has emerged in recent years and could prove to have considerable value to both banks and customers. Thus, this study recognises the need to test the main factors that could predict the use of mobile banking as well as how using such a system could contribute to both customer satisfaction and customer loyalty. The conceptual model of this study combines two models (i.e. UTAUT2 and the D&M IS Success Model). A questionnaire survey was conducted to collect the required data from convenience sampling of Saudi bank customers. The main factors-performance expectancy, price value, facilitating conditions, hedonic motivation, habit, system quality and service quality-were found to have a significant impact on actual use behaviour. This study was cross-sectional, therefore future studies should implement longitudinal studies in order to recollect the findings. Further, this study adopted convenience sampling of Saudi M-Banking users. This may adversely impact the issue of generalisability to the whole population. The gap in the M-Banking literature in Saudi Arabia would be bridged by proposing a comprehensive conceptual model that scrupulously clarifies the use of M-Banking from the perspective of Saudi users. Furthermore, this study would consider the adoption of numeric data in order to inferentially analyse them using SEM. This in turn would assist in generalising the findings to the whole Saudi population.

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Section: Social Influence (Si)mentioning

confidence: 99%

Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model

Baabdullah

Alalwan

Rana

et al. 2019

International Journal of Information Management

Self Cite

407

286

View full text Add to dashboard Cite

show abstract

“…rating of reviews, customer's decision is influenced by the qualitative aspect of reviews such as reviewer quality, review quality etc. (Roy et al, 2018). Similarly, the role of review quality and reviewer's characteristics is analysed by Lee & Shin (2014).…”

Section: Related Work and Research Gapmentioning

confidence: 99%

Exploring reviews and review sequences on e-commerce platform: A study of helpful reviews on Amazon.in

Kaushik

Mishra

Rana

et al. 2018

Journal of Retailing and Consumer Services

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Prominent e-commerce platforms allow users to write reviews for the available products. User reviews play an important role in creating the perception of the product and impact the sales. Online reviews can be considered as an important source of e-word of mouth (e-WOM) on ecommerce platforms. Various dimensions of e-WOM on product sales have been examined for different products. Broadly, studies have explored the effect of summary statistics of reviews on product sales using data from various e-commerce platforms. Few studies have utilized other review characteristics as length, valence, and content of the reviews. The sequence of reviews has been hardly explored in the literature. This study investigates the impact of sequence of helpful reviews along with other review characteristics as ratings (summary statistics), volume, informativeness, and valence of reviews on product sales. Hence, a holistic approach has been used to explore the role of summary statistics, volume, content and sequence of reviews on product sales with special emphasis on sequence of reviews. Relevant theories such as message persuasion, cognitive overload and belief adjustment model have also been explored during the construction of the model for review data. The proposed model has been validated using the helpful reviews available on Amazon.in website for various products.

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“…Recent research topics regarding cQA users relate to modeling their areas of expertise and quantifying their impacts on answer selection [3]; how the evolution of their roles in the community impacts the content relevance between the answerer and the question [4]; the intimacy between askers and answerers [5]. From another angle, current research has focused its attention on discovering informative features of genuine experts [6][7][8], and discovering patterns of interactions between community fellows [9]. Contrary to the vast bulk of recent research, we take the lead on studying the challenges faced by supervised models when discovering discriminative patterns of the age demographics of cQA members.…”

Section: Related Workmentioning

confidence: 99%

Coming to Grips with Age Prediction on Imbalanced Multimodal Community Question Answering Data

2021

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For almost every online service, it is fundamental to understand patterns, differences and trends revealed by age demographic analysis—for example, take the discovery of malicious activity, including identity theft, violation of community guidelines and fake profiles. In the particular case of platforms such as Facebook, Twitter and Yahoo! Answers, user demographics have impacts on their revenues and user experience; demographics assist in ensuring that the needs of each cohort are fulfilled via personalizing and contextualizing content. Despite the fact that technology has been made more accessible, thereby becoming evermore prevalent in both personal and professional lives alike, older people continue to trail Gen Z and Millennials in its adoption. This trailing brings about an under-representation that has a harmful influence on the demographic analysis and on supervised machine learning models. To that end, this paper pioneers attempts at examining this and other major challenges facing three distinct modalities when dealing with community question answering (cQA) platforms (i.e., texts, images and metadata). As for textual inputs, we propose an age-batched greedy curriculum learning (AGCL) approach to lessen the effects of their inherent class imbalances. When built on top of FastText shallow neural networks, AGCL achieved an increase of ca. 4% in macro-F1-score with respect to baseline systems (i.e., off-the-shelf deep neural networks). With regard to metadata, our experiments show that random forest classifiers significantly improve their performance when individuals close to generational borders are excluded (up to 20% more accuracy); and by experimenting with neural network-based visual classifiers, we discovered that images are the most challenging modality for age prediction. In fact, it is hard for a visual inspection to connect profile pictures with age cohorts, and there are considerable differences in their group distributions with respect to meta-data and textual inputs. All in all, we envisage that our findings will be highly relevant as guidelines for constructing assorted multimodal supervised models for automatic age recognition across cQA platforms.

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Identifying reputation collectors in community question answering (CQA) sites: Exploring the dark side of social media

Abstract: N. (2018). Identifying reputation collectors in community question answering (CQA) sites: Exploring the dark side of social media. International Journal of Information Management, 42, 25-35. http://dx.

Cited by 32 publications

References 57 publications

Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model

Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model

Exploring reviews and review sequences on e-commerce platform: A study of helpful reviews on Amazon.in

Coming to Grips with Age Prediction on Imbalanced Multimodal Community Question Answering Data

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