Conference PaperPDF Available

The Differential Effects of Cryptocurrency Incentives in Blockchain Social Networks



While blockchain technology entails transformative potential in many domains, little is known about how the economic mechanisms and governance structures embedded in blockchains affect user behavior. In this paper, we study how blockchain-based incentives impact the user's content creation and curation behavior on social networks. Collecting and analyzing data from 113,209 postings on Steem, a major blockchain social network, we examine how cryptocurrency incentives embedded in blockchain influence the information quality of user-generated content. The preliminary results indicate that different types of cryptocurrencies (namely liquid, vested, and stable cryptocurrency) impact information quality in different ways. We discuss possible implications and ways forward.
Differential Effects of Cryptocurrency Incentives in Blockchain Social Networks
SIGBPS 2019 Workshop on Blockchain and Smart Contract, Munich 2019 1
The Differential Effects of Cryptocurrency
Incentives in Blockchain Social Networks
Rongen (Sophia) Zhang
Georgia State University
Atlanta, Georgia
Junyoung Park
Georgia State University
Atlanta, Georgia
Raffaele Fabio Ciriello
IT University of Copenhagen
Copenhagen, Denmark
While blockchain technology entails transformative potential in many domains, little is
known about how the economic mechanisms and governance structures embedded in
blockchains affect user behavior. In this paper, we study how blockchain-based incentives
impact the user’s content creation and curation behavior on social networks. Collecting
and analyzing data from 113,209 postings on Steem, a major blockchain social network,
we examine how cryptocurrency incentives embedded in blockchain influence the
information quality of user-generated content. The preliminary results indicate that
different types of cryptocurrencies (namely liquid, vested, and stable cryptocurrency)
impact information quality in different ways. We discuss possible implications and ways
Blockchain is a foundational technology enabling new modes of value creation for individuals,
organizations, and society (Beck et al. 2017). Through a distributed ledger, blockchain technology enables
transparency and irreversibility of records, intermediary-free transactions, pseudonymity, and
computational logic (Ilansiti and Lakhani 2017). While blockchain technology is still in its infancy, many
organizations have started to experiment with its potential in various industries.
One such application is the Blockchain Social Network (hereafter BSN), a blockchain-based social media
platform that provides economic mechanisms and governance structures for user participation and content
contribution (Ciriello et al. 2018). With growing skepticism about the security and privacy of user data on
social media platforms, BSN have gained attention as an alternative digital platform, without any single
central entity that can control user information. Another distinctive feature of BSN is that users can earn
cryptocurrency rewards by creating and ‘curating’ content via upvoting (similar to ‘liking’ on Facebook).
Such cryptocurrency incentive mechanisms enable the study of new phenomena regarding how an
economic mechanism embedded in a blockchain affects user behavior in social networks, which much to be
explored (Beck et al. 2018).
The openness of many traditional digital platforms invites broad participation with little or no evaluation,
allowing for free and democratized content creation, but also making it difficult to ensure a high level of
information quality of the content created on such platforms (Lukyanenko et al., 2014). Moreover, due to a
lack of monetary rewards for user-generated content (UGC) creation on many digital platforms, it is
challenging to design appropriate incentives that motivate qualified casual participants to contribute UGC
Differential Effects of Cryptocurrency Incentives in Blockchain Social Networks
SIGBPS 2019 Workshop on Blockchain and Smart Contract, Munich 2019 2
of high information quality (Lukyanenko et al. 2014). In this light, BSNs with cryptocurrency incentives
might be able to motivate users to contribute value.
The goal of this paper is to find out whether the cryptocurrency incentive mechanism implemented in BSN
effectively incentivizes users to create quality content. To this end, we examine the differential effects of
different types of cryptocurrency in BSN on user behavior. Initial exploratory studies have provided
preliminary insight into the need and possible ways to design BSNs with economic mechanisms and
governance structures that promote prosocial behavior (e.g. Beck et al. 2018; Ciriello et al. 2018). However,
with many blockchains in their infancy, empirical research on how these economic mechanisms affect user
behavior on a large scale is still scarce (Thelwall 2018).
Since one critical contribution in a social media context is the creation of high-quality content, we use
information quality as a focal construct for measuring the effects of BSN-provided incentives. Existing
studies have focused mostly on the behavior of Bitcoin or very few cryptocurrencies (ElBahrawy et al. 2017).
Although prior UGC literature has extensively investigated the motivation of user contribution behavior in
online communities, such as extrinsic and monetary incentives, little is still known about the differential
effects of cryptocurrencies with different characteristics on information quality of the content in
blockchain-based online community. Therefore, we raise and address the research question :
RQ: How do different types of cryptocurrency incentives provided by blockchain social networks
influence the information quality of users’ created content?
Hypothesis Development
Among the many BSNs launched in recent years, we focus on Steem (, one of the largest and most
widely known ones. Launched in 2016, Steem enables creation, curation, and consumption of multimedia
content via public and permissionless blockchain database with a built-in incentive mechanism and a
reputation system. The Steem blockchain offers a decentralized rewarding system that provides
cryptocurrency incentives for content creation and curation (Ciriello et al., 2018). It rewards user
participation and contribution based on community evaluations (Larimer et al., 2018). Being essentially a
multipurpose platform enabling many different decentralized applications (or dApps), the most widely used
social media application on the Steem blockchain is Steemit ( Steemit’s functions for content
sharing and social networking are similar to those of Facebook or Reddit (Thewall 2018).
Cryptocurrency can be one type of monetary incentives which motivates users to create better quality
content in BSN. With limited time and resources at hand, a user’s contributions to the platform can be
affected by cryptocurrency rewards for two behaviors, namely content creation and curation. Such focus
can affect the quality of posting because creating a better quality posting requires more time and effort.
Therefore, we are interested in the effects of users’ previous posting rewards and curation rewards on the
information quality of posting in BSN. A user with more previous posting rewards will have more incentive
to invest the time and effort in content creation. On the contrary, previous curation reward will drive a user
to focus more on curation behavior, which will lower the quality of posting. Therefore, we hypothesize:
H1a: Users’ previous posting cryptocurrency reward is positively associated with the information quality
of UGC.
H1b: Users’ previous curation cryptocurrency reward is positively associated with the information
quality of UGC.
Moreover, the platform runs three native cryptocurrency tokens with different characteristics, which users
can acquire as a reward for contribution and by transactions.
1) STEEM: STEEM is the fundamental unit of account on Steem. The STEEM token is a liquid
cryptocurrency that users can transact as a form of payment or trade for other external tokens,
cryptocurrencies, and fiat money, such as US Dollars.
2) STEEM Power (SP): Users can convert their STEEM into SP by committing them to a vesting
schedule. SP grants users stronger voting rights. SP is non-transferable and can only be withdrawn by
converting the SP back to liquid STEEM in 13 equal weekly payments.
3) Steem Blockchain Dollar (SBD): SBD is a stable cryptocurrency pegged to the value of the US dollar
that can be viewed as a form of debt with a relatively static value.
Differential Effects of Cryptocurrency Incentives in Blockchain Social Networks
SIGBPS 2019 Workshop on Blockchain and Smart Contract, Munich 2019 3
Based on the characteristics of the abovementioned cryptocurrencies, we categorize STEEM, SP, and SBD
as Liquid Cryptocurrency, Stable Cryptocurrency, and Vested Cryptocurrency, respectively. We hypothesize
about the impact of a user’s balances of the three types of cryptocurrency on information quality of UGC.
First, as a user hold more Liquid Cryptocurrency, the user will hope and try to increase the value of the
cryptocurrency to gain more benefit. In BSN, one major approach to increase the value of the platform is to
contribute better quality postings to the platform. Therefore, we hypothesize that:
H2a: The Liquid Cryptocurrency balance is positively associated with the information quality of UGC.
Stable Cryptocurrency was introduced to mitigate the infamous price volatility issue. A user with Stable
Cryptocurrency can rely on its relatively stable value. Therefore, the user with more Stable Cryptocurrency
will be more motivated to create better quality posting to acquire more rewards. So, we hypothesize that:
H2b: The Stable Cryptocurrency balance is positively associated with the information quality of UGC.
Finally, Vested Cryptocurrency was designed with the purpose of stabilizing the platform value. Users with
Vested Cryptocurrency can be viewed as equity-holders of the platform so that they are more involved in
the platform as stakeholders. A user with more Vested Cryptocurrency is likely to be more motivated to
create better quality content to increase the value of the platform, so that the value of their equity will
increase. Therefore, we hypothesize that:
H2c: The Vested Cryptocurrency balance is positively associated with the information quality of UGC.
We designed a Python-based web crawler using the blockchain explorer API provided at to
extract all postings in English on the Steem blockchain spanning three periods: 08 April - 28 April, 17 May
- 2 June, 4 June - 10 June (2019). The texts from the postings went through basic pre-processing steps
including the removals of unique characters, slang, emoticons, and numbers, and stop words.
Because this study examines the impact of cryptocurrency incentives on the objective quality of posted
information, rather than subjective evaluation of it, we attempt to capture the information quality from the
measures directly accessible from the contents (Agichtein et al. 2008). In doing so, we use multiple
linguistic and multimedia measures. As the linguistic measures, we extracted the number of unique words
(henceforth ‘length’), the Flesch Reading Ease Score (henceforth ‘readability’), and the Shannon entropy of
trigrams (henceforth ‘entropy’), which are used in online review literature as indicators of information
quality (e.g., Johnson et al. 2015; Singh et al. 2014). As for the multimedia measures, we extracted the
number of images, external links, and hashtags used in each post, which provide additional information
than plain texts (Janze and Risius 2017). Because the six measures use different units, the overall
information quality was constructed by standardizing each of the six measures and then calculating the
average of them.
Our explanatory variables include the author’s previous cryptocurrency reward and three types of
cryptocurrency balance. We used the values of an author’s cumulative rewards from their previous postings
and curation activities as the two types of previous cryptocurrency reward. Author’s balances of the three
types of cryptocurrency (i.e., liquid, stable, and vested) were measured as the amount of STEEM, SBD, and
SP, respectively, that the author holds at the time that the posting was created.
Finally, we control for the authors’ reputation score, number of followers, tenure in the platform (i.e., days
since registration), number of previous postings, the category of the post, and the creation date of the
posting. Among the 279,814 postings collected, we removed those with missing values and with readability
scores below 0 or above 100. Overall, our final dataset includes 113,029 postings from 12,334 authors.
The econometric model for the antecedents of posting information quality is:
where the subscript i represents posting.
Differential Effects of Cryptocurrency Incentives in Blockchain Social Networks
SIGBPS 2019 Workshop on Blockchain and Smart Contract, Munich 2019 4
Preliminary Results
Table 1 summarizes the results of the OLS regression for the antecedents of information quality. Model 1
includes only the control variables. We find that reputation and number of followers are positively
associated with information quality, whereas tenure shows negative association. Model 2 represents the full
model with the variables of interest. Both previous posting reward and previous curation reward are
negatively associated with information quality, rejecting both H1a and H1b. That is, receiving higher
rewards from both content creation and curation efforts might crowd out the user’s intrinsic motivation to
craft good-quality content.
Table 1. Results of the OLS Regression for the Antecedents of Information Quality
Model 2
(DV - IQ)
Model 3
(DV - Linguistic
Model 4
(DV - Multimedia
Previous posting
Previous curation
STEEM (liquid)
SP (vested) balance
SBD (stable) balance
Number of followers
Number of previous
Category dummy
Date dummy
Adjusted R-squared
n=113,209, *p<0.05, **p<0.005
Regarding the role of cryptocurrency balance, one major surprising finding is that SP (vested) and SBD
(stable) balances are significantly positively associated with information quality, but STEEM (liquid)
balance is negatively associated with information quality. Therefore, H2b and H2c are supported, while
H2a is not supported. This result suggests that different types of cryptocurrency play different roles as
incentives for creating better quality postings. It has been acknowledged that the volatility of a
Differential Effects of Cryptocurrency Incentives in Blockchain Social Networks
SIGBPS 2019 Workshop on Blockchain and Smart Contract, Munich 2019 5
cryptocurrency generates risk, which discourages consumers from holding the cryptocurrency for a long
time (Devries 2016). In that sense, users with more Liquid Cryptocurrency (i.e., STEEM) that is volatile
might be less motivated to contribute with higher quality postings.
As a post-hoc analysis, we present the results for the analysis where we run separate models for information
quality measured using only linguistic (Model 3) and multimedia measures (Model 4). The results for
linguistic information quality are consistent with the main result. The results for Model 4 shows that
STEEM (liquid) balance affect multimedia information quality negatively while SBD (stable) affects
multimedia information quality positively. Also, the coefficients for SP (vested) balance and previous
posting and curation rewards are insignificant. Overall, the results for Model 3 and Model 4 indicates that
linguistic information quality is the driving force of the overall information quality.
Intended Contributions
In further developing this work, this study will make the following theoretical contributions. First, it will
illustrate blockchain-enabled incentives provided in blockchain economies and their effects on user
behavior. While the existing blockchain discourse is still nascent and often focuses on the proof of concepts
and potential use cases, this study will provide empirical insights. Second, this study will categorize
different cryptocurrencies based on their characteristics of liquidity and volatility, which offers a novel
perspective to future research on blockchain and cryptocurrency. Third, this study will unpack the
differential effects of cryptocurrency incentives with different characteristics on information quality of
content in blockchain-based online communities.
Moreover, our study will inform the designers of BSN systems about the interrelated effects of different
incentives on user behavior. Practitioners and design-oriented researchers can build on our study and
engage in the design of effective incentive schemes for BSNs. For example, digital platforms that wish to
adopt cryptocurrency incentive mechanisms should be cautious about implementing rewards for curation
and creation to avoid the here-identified negative effect of curation rewards. Also, introducing stable and
vested cryptocurrency can be effective to facilitate the improvement of content quality in blockchain-based
online communities.
Agichtein, E., Castillo, C., Donato, D., Gionis, A., and Mishne, G. 2008. “Finding High-Quality Content in Social
Media,” in Proceedings of the 2008 International Conference on Web Search and Data Mining, Palo Alto, CA, pp.
Beck, R., Avital, M., Rossi, M., and Thatcher, J. B. 2017. “Blockchain Technology in Business and Information
Systems Research,” Business & Information Systems Engineering (59:6), Springer Fachmedien Wiesbaden, pp.
Beck, R., Müller-Bloch, C., King, J. L., Beck, R., Müller-Bloch, C., King, J. L., and Thatcher, J. 2018. “Governance in
the Blockchain Economy: A Framework and Research Agenda.,” Journal of the Association for Information
Systems (19: March), pp. 236.
Ciriello, R. F., Beck, R., and Thatcher, J. B., 2018. “The Paradoxical Effects of Blockchain Technology on Social
Networking Practices,” in Proceedings of the 39th International Conference on Information Systems, San
Francisco, CA, pp. 117.
ElBahrawy, A., Alessandretti, L., Kandler, A., Pastor-Satorras, R., and Baronchelli, A. 2017. “Evolutionary Dynamics
of the Cryptocurrency Market,” Royal Society Open Science (4:11), p. 170623.
Ilansiti, M., and Lakhani, K. R. 2017. “The Truth About Blockchain,” Harvard Business Review (February).
Janze, C., Risius, M., 2017. Automatic Detection of Fake News on Social Media Platforms,” in Proceedings of the
Pacific Asia Conference on Information Systems, p. 261.
Johnson, S. L., Safadi, H., Faraj, S. 2015. “The Emergence of Online Community Leadership,” Information Systems
Research (26:1), pp. 165-187.
Larimer, D., Scott, N., Zavgorodnev, V., Johnson, B., Calfee, J., Vandeberg, M. 2018. Steem: An incentivized,
blockchain-based social media platform,” Self-published, March. (,
accessed Novermber 8, 2019).
Lukyanenko, R., Parsons, J., and Wiersma, Y. F. 2014. “The IQ of the Crowd: Understanding and Improving
Information Quality in Structured User-Generated Content,” Information Systems Research (25:4), pp. 669689.
Singh, P. V., Sahoo, N., Mukhopadhyay, T. 2014. “How to Attract and Retain Readers in Enterprise Blogging?,”
Information Systems Research (25:1), pp. 35-52.
Thelwall, M., 2018. “Can Social News Websites Pay for Content and Curation? The SteemIt Cryptocurrency Model,”
Journal of Information Science (44:6), pp. 736751.
... Aside from the relationships among users, [20] studies block producers (witnesses) and highlights their social impact on the platform. Other works are more focused on the economic aspects: Ciriello et al. [21] and Thelwall et al. [22] analyze the relationship between rewards and content, while Li et al. [23] describes and analyzes the networked structures behind the Steemit rewarding system. ...
Full-text available
A shift of paradigm is running over online social platforms: the over-centralization of these platforms is leaving room for decentralized solutions based on blockchain technologies, such as blockchain-based online social networks—BOSNs. Among the many unknown aspects of these techno-social systems, the objective of this study is to propose an analytical framework to assess the impact of the cryptocurrencies linked to a BOSN platform on the evolution of its social network and on the behavior of their users, in terms of production of content and/or its promotion through a voting and rewarding system. The framework has been applied to Steemit, one of the most widespread BOSNs, from which we collected three-year-long high-resolution data on its evolution along with the price of its main cryptocurrencies. On users’ activities extracted from these longitudinal data, we applied a time-series correlation analysis and a correlation analysis between the action allocation strategies and the obtained rewards, in the case of most central accounts. The analysis has highlighted pieces of evidence of the influence of the cryptocurrency price on users’ actions, particularly on actions that shape the structure of the social networks. Second, we also found highly rewarded users prefer actions related to the promotion of content rather than the creation of high-quality content, exploiting the reward distribution mechanisms implemented by the platform. These findings highlight that the shift of paradigm towards blockchain and cryptocurrency technologies might strengthen the influence of financial and economic factors rather than relational/social aspects on the evolution of these new complex techno-social systems.
... Choi, Guo and Luo identify issues around privacy and unstructured data collection [44]. Scholars tackle the incentive system of social exchanges and relationships in social media [45,46]. Guidi et al. identify the issue of data islands, also called "walled gardens", and try to overcame by adding a P2P social overlay built by exploiting the real life of the social network's users [47]. ...
Full-text available
Given the emerging nature of integrating Blockchain Technology (“BCT”) into several business fields concerning the interaction between companies and their customers, this study aims to investigate the applications of BCT in marketing through an accurate procedure of locating, selecting and analyzing existing companies using BCT in marketing. A sample that consists of 800 companies was identified using web-scraping methods. The data set was collected from ICO websites as well as from an existing, older landscape of applications. The data set was then intensively analyzed in order to be categorized into five fields of marketing technology. Advertising and ecommerce outgrew the other fields of social & relationship, content & experience and data in absolute numbers, revealing the focus of practitioners in the past as well as gaps for the future. The authors provided future directions for researchers on and development of tools to systematically generate knowledge and improve the application of BCT and the work of practitioners in marketing.
... Steemit is a BOSM launched the 24th of March 2016 [14]- [16], and has features similar to Reddit and Medium. ...
Nowadays, with the emergence of Web 3.0 and the metaverse, we collectively witnessed the explosive development of the decentralised autonomous organisation and the blockchain business model. Particularly, the advancement of technologies has further given birth to a novel form of social platform as blockchain-enabled social media (i.e., SocialFi), which is growing both in size and number of users. Accordingly, the rapid development of these blockchain-enabled social media firms illustrates the requirement to better understand the reasons behind this increase and the innovative practices and strategies of firms in this emerging field. Using the case of Pixie – the world’s first fully functional decentralised photo and video sharing social network based on blockchain technology, this insight paper identifies a conceptual model of blockchain-enabled social media that is useful for illustrating the successful business strategy and operations of firms. Particularly, the identified model employs four pillars of innovation as fundamental technologies, governance and operations, incentive mechanism design, and organisational structure and performance. Based on this crypto economy social media model, the study further presents the main challenges, discusses the implications based on agency theory, as well as highlights several directions for future research associated with blockchain-enabled social media.
Conference Paper
Full-text available
Blockchain technology is a promising, yet not well understood, enabler of large-scale societal and economic change. For instance, blockchain makes it possible for users to securely and profitably share content on social media platforms. In this study, we explore how blockchain enables and constrains social networking practices by means of an in-depth qualitative study of Steem, a major Blockchain Social Network (BSN). From that, we identify three paradoxical effects of BSN: 1) Freedom and Captivity, 2) Abundance and Scarcity, and 3) Peace and War. Via a dialectic synthesis of the three paradoxes, we theorize the effects of blockchain technology on social networking practices. We discuss theoretical implications for research on blockchain, social media, and online communities and define a path for research on BSN. We also discuss theoretical and practical implications by illustrating the paradoxical effects of using BSN and suggesting appropriate coping strategies.
Conference Paper
Full-text available
This study investigates how fake news shared on social media platforms can be automatically identified. Drawing on the Elaboration Likelihood Model and previous studies on information quality, we develop and test an explorative research model on Facebook news posts during the U.S. presidential election 2016. The study examines how cognitive, visual, affective and behavioral cues of the news posts as well as of the addressed user community can be used by machine learning classifiers to identify fake news fully automatically. The best performing configurations achieve a stratified 10-fold cross validated predictive accuracy of more than 80%, and a recall rate (share of correctly identified fake news) of nearly 90% on a balanced data sample solely based on data directly available on Facebook. Platform operators and users can draw on the results to identify fake news on social media platforms - either automatically or heuristically.
Full-text available
The cryptocurrency market has reached a record of $\$$54 billion in 2017 after months of steady growth. However, a comprehensive analysis of the whole system has been lacking so far, since most studies have focused on the behaviour of one (Bitcoin) or few cryptocurrencies. Here we consider the entire market and analyse the behaviour of $\sim$ 1,500 cryptocurrencies introduced since April 2013. We reveal that, while new cryptocurrencies appear and disappear continuously and the market share of Bitcoin has been constantly decreasing, several statistical properties of the market have been stable for years. These include the number of active cryptocurrencies, the market share distribution and the turnover of cryptocurrencies. Finally, we adopt an ecological perspective and show that the so-called 'neutral model' of evolution, despite its simplicity, reproduces a number of key empirical observations. We anticipate that our results will be of interest to researchers interested in the study and modelling of the structural properties of the cryptocurrency market.
Full-text available
Compared to traditional organizations, online community leadership processes and how leaders emerge are not well studied. Previous studies of online leadership have often identified leaders as those who administer forums or have high network centrality scores. Although communication in online communities occurs almost exclusively through written words, little research has addressed how the comparative use of language shapes community dynamics. Using participant surveys to identify leading online community members, this study analyzes a year of communication network history and message content to assess whether language use differentiates leaders from other core community participants. We contribute a novel use of textual analysis to develop a model of language use to evaluate the utterances of all participants in the community. We find that beyond communication network position-in terms of formal role, centrality, membership in the core, and boundary spanning-those viewed as leaders by other participants, post a large number of positive, concise posts with simple language familiar to other participants. This research provides a model to study online language use and points to the emergent and shared nature of online community leadership.
Full-text available
User-generated content (UGC) is becoming a valuable organizational resource, as it is seen in many cases as a way to make more information available for analysis. To make effective use of UGC, it is necessary to understand information quality (IQ) in this setting. Traditional IQ research focuses on corporate data and views users as data consumers. However, as users with varying levels of expertise contribute information in an open setting, current conceptualizations of IQ break down. In particular, the practice of modeling information requirements in terms of fixed classes, such as an Entity-Relationship diagram or relational database tables, unnecessarily restricts the IQ of user-generated data sets. This paper defines crowd information quality (crowd IQ), empirically examines implications of class-based modeling approaches for crowd IQ, and offers a path for improving crowd IQ using instance-and-attribute based modeling. To evaluate the impact of modeling decisions on IQ, we conducted three experiments. Results demonstrate that information accuracy depends on the classes used to model domains, with participants providing more accurate information when classifying phenomena at a more general level. In addition, we found greater overall accuracy when participants could provide freeform data compared to a condition in which they selected from constrained choices. We further demonstrate that, relative to attribute-based data collection, information loss occurs when class-based models are used. Our findings have significant implications for information quality, information modeling, and UGC research and practice.
Conference Paper
Full-text available
The quality of user-generated content varies drastically from excellent to abuse and spam. As the availability of such content increases, the task of identifying high-quality content sites based on user contributions --social media sites -- becomes increasingly important. Social media in general exhibit a rich variety of information sources: in addition to the content itself, there is a wide array of non-content information available, such as links between items and explicit quality ratings from members of the community. In this paper we investigate methods for exploiting such community feedback to automatically identify high quality content. As a test case, we focus on Yahoo! Answers, a large community question/answering portal that is particularly rich in the amount and types of content and social interactions available in it. We introduce a general classification framework for combining the evidence from different sources of information, that can be tuned automatically for a given social media type and quality definition. In particular, for the community question/answering domain, we show that our system is able to separate high-quality items from the rest with an accuracy close to that of humans
SteemIt is a Reddit-like social news site that pays members for posting and curating content. It uses micropayments backed by a tradeable currency, exploiting the Bitcoin cryptocurrency generation model to finance content provision in conjunction with advertising. If successful, this paradigm might change the way in which volunteer-based sites operate. This article investigates 925,092 new members’ first posts for insights into what drives financial success in the site. Initial blog posts on average received US$0.01, although the maximum accrued was US$20,680.83. Longer, more sentiment-rich or more positive comments with personal information received the greatest financial reward in contrast to more informational or topical content. Thus, there is a clear financial value in starting with a friendly introduction rather than immediately attempting to provide useful content, despite the latter being the ultimate site goal. Follow-up posts also tended to be more successful when more personal, suggesting that interpersonal communication rather than quality content provision has driven the site so far. It remains to be seen whether the model of small typical rewards and the possibility that a post might generate substantially more are enough to incentivise long-term participation or a greater focus on informational posts in the long term.
We investigate the dynamics of blog reading behavior of employees in an enterprise blogosphere. A dynamic model is developed and calibrated using longitudinal data from a Fortune 1,000 IT services firm. Our modeling framework allows us to segregate the impact of textual characteristics (sentiment and quality) of a post on attracting readers from retaining them. We find that the textual characteristics that appeal to the sentiment of the reader affect both reader attraction and retention. However, textual characteristics that reflect only the quality of the posts affect only reader retention. We identify a variety-seeking behavior of blog readers where they dynamically switch from reading on one set of topics to another. The modeling framework and findings of this study highlight opportunities for the firm to influence blog-reading behavior of its employees to align it with its goals. Overall, this study contributes to improved understanding of reading behavior of individuals in communities formed around user generated content.