Analyzing market performance via social media: a case study of a banking industry crisis

Analyzing market performance via social media has attracted a great deal of attention in the finance and machine-learning disciplines.However,the vast majority of research does not consider the enormous influence a crisis has on social media that further affects the relationship between social media and the stock market.This article aims to address these challenges by proposing a multistage dynamic analysis framework.In this framework,we use an authorship analysis technique and topic model method to identify stakeholder groups and topics related to a special firm.We analyze the activities of stakeholder groups and topics in different periods of a crisis to evaluate the crisis’s influence on various social media parameters.Then,we construct a stock regression model in each stage of crisis to analyze the relationships of changes among stakeholder groups/topics and stock behavior during a crisis.Finally,we discuss some interesting and significant results,which show that a crisis affects social media discussion topics and that different stakeholder groups/topics have distinct effects on stock market predictions during each stage of a crisis.     

How Does Corporate Reputation Affect Customer Loyalty in a Corporate Crisis?

It is widely accepted that corporate reputation plays an important role in determining the impact of crises on firms. Crises may erode corporate reputation. However, reputation may also attenuate the negative effects of crises. This study investigates how corporate reputation moderates the relationship between crisis occurrence and customer loyalty which is expected to decrease given a crisis. Drawing on opposing theories, namely dissonance theory and expectancy‐violation, we conduct a scenario experiment set in the airline industry. Results demonstrate that the moderating effect is weaker in the case of a favourable corporate reputation. This may indicate that a pre‐existing favourable reputation does not shield the firm from the negative effects of the crisis, but may rather present a liability because customers have higher expectations with regard to well‐reputed firms. Contrary to that, ill‐reputed firms have less to lose in the case of a crisis and suffer comparatively smaller decreases in customer loyalty. Marketing management might take into account the role of crisis and reputation management for customer bonding strategies while crisis management should recognize the importance of reputation effects in crises given their impact on customer loyalty and firm profitability.     

Event detection over twitter social media streams

In recent years, microblogs have become an important source for reporting real-world events. A real-world occurrence reported in microblogs is also called a social event. Social events may hold critical materials that describe the situations during a crisis. In real applications, such as crisis management and decision making, monitoring the critical events over social streams will enable watch officers to analyze a whole situation that is a composite event, and make the right decision based on the detailed contexts such as what is happening, where an event is happening, and who are involved. Although there has been significant research effort on detecting a target event in social networks based on a single source, in crisis, we often want to analyze the composite events contributed by different social users. So far, the problem of integrating ambiguous views from different users is not well investigated. To address this issue, we propose a novel framework to detect composite social events over streams, which fully exploits the information of social data over multiple dimensions. Specifically, we first propose a graphical model called location-time constrained topic (LTT) to capture the content, time, and location of social messages. Using LTT, a social message is represented as a probability distribution over a set of topics by inference, and the similarity between two messages is measured by the distance between their distributions. Then, the events are identified by conducting efficient similarity joins over social media streams. To accelerate the similarity join, we also propose a variable dimensional extendible hash over social streams. We have conducted extensive experiments to prove the high effectiveness and efficiency of the proposed approach.     

Exploring the effect of user engagement in online brand communities: Evidence from Twitter

Social media such as forums, blogs and microblogs has been increasingly used for public information sharing and opinions exchange nowadays. It has changed the way how online community interacts and somehow has led to a new trend of engagement for online retailers especially on microblogging websites such as Twitter. In this study, we investigated the impact of online retailers' engagement with the online brand communities on users' perception of brand image and service. Firstly, we analysed the overall sentiment trends of different brands and the patterns of engagement between companies and customers using the collected tweets posted on a popular social media platform, Twitter. Then, we studied how different types of engagements affect customer sentiments. Our analysis shows that engagement has an effect on sentiments that associate with brand image, perception and customer service of the online retailers. Our findings indicate that the level, length, type and attitude of retailers' engagement with social media users have a significant impact on their sentiments. Based on our results, we derived several important managerial and practical implications.     

How do social commerce-IT capabilities influence firm performance? Theory and empirical evidence

We theorized that the development of two contemporary social commerce-IT capabilities (social media and e-commerce) enables firms to engage online customers to improve their firm performance. We tested this theory by employing a secondary dataset on a sample of U.S. firms. The empirical analysis supported our theory in both examining the effects of social media and e-commerce as two individual capabilities and as two complementary capabilities. This study provides a unique organizational theory and empirical evidence on how social commerce-IT capabilities influence firm performance through the online engagement of customers.     

Adoption of Low Earth Orbit Satellite Systems: A Diffusion Model under Competition

Low Earth Orbit Satellite (LEOS) systems have started providing communication with one phone number throughout the world. In this paper, the diffusion process of the two LEOS systems is analyzed under competition. We simulate the diffusion process under different scenarios. In these scenarios, we analyze issues related to the timing of product introduction, technology advantage and potential customer base. A model of the potential customer base with network externality is presented. We found that the timing of product introduction can have significant impact on the follower in the market. We found that a follower firm with more advanced technology would have higher probability to succeed in competing against the first mover. In addition, the increase in the potential customer base favors the firm with advanced technology. The network externality effect in the growth of the customer base favors both firms but could be an barrier for the follower to create a critical mass and beat the incumbent firm.     

Use of Twitter in the Cameroon Anglophone crisis

ABSTRACT

A growing body of literature shows that social media plays a key role during crises and conflicts. In addition to traditional media, social media are used to mobilise people for a common cause and to communicate vital information. Very little is known about social media use during crises in the sub-Saharan African context. This article presents how Twitter is being used in the ongoing Cameroon Anglophone Crisis by several groups including the government, Anglophone activists, media organisations, and everyday citizens. Using critical theoretical perspectives to examine tweets from 1 September 2016 to 31 December 2018, this article identifies key themes. These include: placement of the crisis in a contested, historical context; debates about naming the crisis; key concepts; depiction of several forms of violence; and potential options for resolution. Social media is being used by the government, Anglophone activists, and non-affiliated people to sway public opinions on the crisis and solicit the attention of local, Diaspora, and broader international communities. Social media use has loosened the grip of governmental control of media messaging and expanded the public narratives available in Cameroon, yet at the time of the writing, this does not appear to have lessened the impact of the crisis.     

Regional Sentiment Bias in Social Media Reporting During Crises

Crisis events such as terrorist attacks are extensively commented upon on social media platforms such as Twitter. For this reason, social media content posted during emergency events is increasingly being used by news media and in social studies to characterize the public’s reaction to those events. This is typically achieved by having journalists select ‘representative’ tweets to show, or a classifier trained on prior human-annotated tweets is used to provide a sentiment/emotion breakdown for the event. However, social media users, journalists and annotators do not exist in isolation, they each have their own context and world view. In this paper, we ask the question, ‘to what extent do local and international biases affect the sentiments expressed on social media and the way that social media content is interpreted by annotators’. In particular, we perform a multi-lingual study spanning two events and three languages. We show that there are marked disparities between the emotions expressed by users in different languages for an event. For instance, during the 2016 Paris attack, there was 16% more negative comments written in the English than written in French, even though the event originated on French soil. Furthermore, we observed that sentiment biases also affect annotators from those regions, which can negatively impact the accuracy of social media labelling efforts. This highlights the need to consider the sentiment biases of users in different countries, both when analysing events through the lens of social media, but also when using social media as a data source, and for training automatic classification models.     

Should firms invest in social commerce? An integrative perspective

Integrating resource-based view and opportunity–motivation–ability framework, we theorize that social commerce represents firms’ opportunity to access valuable social media resources and gain a competitive advantage. We further argue that product uncertainty and firm reputation indicate firms’ motivation and ability, respectively, to use the social media resources, affecting the extent to which the competitive advantage can be realized. An event study of 275 social commerce initiatives announced between 2006 and 2011 supports our arguments, showing that social commerce increases firms’ stock returns, but such increases are more significant for firms selling products with high uncertainty and having high reputation.     

IT-enabled knowledge ambidexterity and innovation performance in small U.S. firms: The moderator role of social media capability

This study examines the impact of information technology (IT)-enabled knowledge ambidexterity on innovation performance, and the potential moderator role of social media capability on a sample composed of 100 small U.S. firms. The empirical analysis suggests that IT infrastructure enables the firm to explore new knowledge and exploit existing/new knowledge to innovate more and better. We also find that social media capability has a positive moderator role in this equation: IT infrastructure and social media capabilities work together to enable knowledge ambidexterity.     

Social sentiment sensor: a visualization system for topic detection and topic sentiment analysis on microblog

As a new form of social media, microblogging provides platform sharing, wherein users can share their feelings and ideas on certain topics. Bursty topics from microblogs are the results of the emerging issues that instantly attract more followers and more attention online, which provide a unique opportunity to gauge the relation between expressed public sentiment and hot topics. This paper presents a Social Sentiment Sensor (SSS) system on Sina Weibo to detect daily hot topics and analyze the sentiment distributions toward these topics. SSS includes two main techniques, namely, hot topic detection and topic-oriented sentiment analysis. Hot topic detection aims to detect the most popular topics online based on the following steps, topic detection, topic clustering, and topic popularity ranking. We extracted topics from the hashtags using a hashtag filtering model because they can cover almost all the topics. Then, we cluster the topics that describe the same issue, and rank the topic clusters via their popularity to exploit the final hot topics. Topic-oriented sentiment analysis aims to analyze public opinions toward the hot topics. After retrieving the topic-related messages, we recognize sentiment for each message using a state-of-the-art SVM (Support Vector Machine) sentiment classifier. Then, we summarize the sentiments for the hot topic to achieve topic sentiment distribution. Based on the above framework and algorithms, SSS produces a real-time visualization system to monitor social sentiments, which is offering the public a new and timely perspective on the dynamics of the social topics.     

Generating and exploiting customer insights from social media data

Previous research has emphasized the virtues of customer insights as a key source of competitive advantage. The rise of customers’ social media use allows firms to collect customer data in an ever-increasing volume and variety. However, to date, little is known about the capabilities required of firms to turn social media data into valuable customer insights and exploit these insights to create added value for customers. Based on the dynamic capabilities perspective, in particular the concept of absorptive capacity (ACAP), the authors conducted multiple case studies of seven mid-sized and large B2C firms in Switzerland and Germany. The results provide an in-depth analysis of the underlying processes of ACAP as well as contingent factors – that is, physical, human and organizational resources that underpin the firms’ ACAP.     

Digital bundling

Increasingly, we see that firms offer many items on information-intensive channels and the Internet. Especially with low-marginal-cost digital goods, bundling may be a beneficial strategy. Different bundles may help customers become more discriminating and maximize profits. However, the marketplace evidence provides mixed observation of bundling rigorously pursued. In this study, we provide a general framework to analyze when and how bundling may be beneficial. We compare and contrast the firm and customer characteristics on bundling strategy. We analyze when individual sales can be beneficial. We find that when costs do not increase relative to the bundle valuation, firms find it beneficial to limit the number of bundles offered in the market. A low (zero) marginal cost firm benefits from offering just one big bundle. Such a firm obtains a higher profit compared to a firm that offers many bundles. With high marginal costs, the number of bundles increases with increasing customer valuation and/or heterogeneity. When a firm offers all the bundles, prices and profit increase as customer heterogeneity and valuation increase. When the number of offered items is high, individual sale (unbundling) may be preferred over bundling and bundling becomes an inferior strategy. Interestingly, a firm may benefit from unbundling the items when customers have higher valuations.     

Sentiment analysis from Customer-generated online videos on product review using topic modeling and Multi-attention BLSTM

With the popularity of social websites and mobile applications including Instagram, YouTube, TikTok, etc., online videos shared by customers presenting their thoughts and reviews on products are posted daily in increasing numbers. Such online videos containing Voice of Customer (VOC) are precious for product designers or managers to capture customer sentiment and understand customer preference. For this purpose, we propose a novel method for analyzing customer sentiment from online videos on product review. Firstly, latent Dirichlet allocation (LDA) modeling is applied to identify the topics from the online videos after data preprocessing. Then sentiment polarity corresponding to each topic of each speaker in videos can be identified using our newly designed multi-attention bi-directional LSTM (BLSTM(MA)), which can better mine complex relationships among a speaker’s sentiments on different topics. This paper is of great practical value for company managers and researchers to better understand a large number of customer opinions on specific products. To explain the application of this method and prove its effectiveness, two cases respectively on smartphones and several published datasets are developed finally.     

Impact of the usage of social media in the workplace on team and employee performance

How does the usage of social media in the workplace affect team and employee performance? To address this cutting edge and up-to-date research question, we ran a quasinatural field experiment, collecting data of two matched-sample groups within a large financial service firm in China. We find that work-oriented social media (DingTalk) and socialization-oriented social media (WeChat) are complementary resources that generate synergies to improve team and employee performance. The instrumental value provided by work-oriented social media is reinforced by the expressive value provided by socialization-oriented social media, which help firms to create business value from information technology investments.     

Competitive Pricing Strategies for Software and SaaS Products

We study the pricing strategies for a software firm and an entrant software-as-a-service (SaaS) firm in two customer markets: the market composed of the incumbent’s past customers and the market of new customers. We build a game theoretical model to investigate how user costs and the quality differential between products affect firms’ pricing in different customer markets. Our findings show that it is not always optimal for the software firm to price discriminate between its old users and the new customers. The entrant firm would be better off acquiring only the new customers when the SaaS quality is sufficiently low.     

The tweets that killed a university: A case study investigating the use of traditional and social media in the closure of a state university

The 12-month discussion surrounding a regional university campus quickly evolved from a suggestion of independence, to a plan, to the ultimate closure of the university. This unique series of events at the University of South Florida Polytechnic (USFP) allows for an investigation of how various forms of media were used during this significant event that impacted college student’s education and immediate future. A campus wide survey was combined with social and online media monitoring to assess the topics, authors, and methods used during prominent discussions during and preceding the closure of USFP. Although social media played a crucial role, the most common format was Twitter and it was used almost exclusively by members of the media itself. Students instead relied on traditional sources to gather information. Additionally, students expressed their opinion utilizing classic methods, such as petitions, foregoing more modern Twitter or Facebook campaigns. It is incorrect to automatically assume younger demographic authorship or utilization of social media technology. Whereas social media use could expand even more over the next decade, identifying authorship remains critical as it is unclear how frequent social media is viewed as an official method of public discussion, especially when politics and higher education collide.     

Firm orientation,community of practice,and Internet-enabled interfirm communication: Evidence from Chinese firms

What motivates firms to develop Internet-enabled interfirm communication? We draw upon the work of Alavi et al. (2005–2006) and propose that the use of the Internet in interfirm communication is influenced by a firm’s firm orientation and its internal communities of practice. Based on data collected from 307 international trade firms in the Beijing area, we find that Internet-enabled interfirm communication is directly driven by internal community of practices and customer orientation, and indirectly by competitor orientation and learning orientation. The internal community of practice is affected by learning orientation and competitor orientation, but not by customer orientation. The present study contributes to the literature by providing empirical investigation on firm’s strategic communications from the perspective of firm orientations, delineating how different firm orientations vary in impacting firm’s strategic communications, and exploring the bridging effect of communities of practices on the influences of firm orientations on knowledge management initiatives.     

Advances in Social Media Research: Past,Present and Future

Social media comprises communication websites that facilitate relationship forming between users from diverse backgrounds, resulting in a rich social structure. User generated content encourages inquiry and decision-making. Given the relevance of social media to various stakeholders, it has received significant attention from researchers of various fields, including information systems. There exists no comprehensive review that integrates and synthesises the findings of literature on social media. This study discusses the findings of 132 papers (in selected IS journals) on social media and social networking published between 1997 and 2017. Most papers reviewed here examine the behavioural side of social media, investigate the aspect of reviews and recommendations, and study its integration for organizational purposes. Furthermore, many studies have investigated the viability of online communities/social media as a marketing medium, while others have explored various aspects of social media, including the risks associated with its use, the value that it creates, and the negative stigma attached to it within workplaces. The use of social media for information sharing during critical events as well as for seeking and/or rendering help has also been investigated in prior research. Other contexts include political and public administration, and the comparison between traditional and social media. Overall, our study identifies multiple emergent themes in the existing corpus, thereby furthering our understanding of advances in social media research. The integrated view of the extant literature that our study presents can help avoid duplication by future researchers, whilst offering fruitful lines of enquiry to help shape research for this emerging field.     

AspectFrameNet: a frameNet extension for analysis of sentiments around product aspects

In the real-world scenarios, customer tries to evaluate a product based on sentiments conveyed by its users or reviewers. AspectFrameNet provides a framework that helps the semantic analysis of text inputs from social feeds and news (Voice of Customer) by disambiguating the contexts in which the lexical units are used. To this end, we have used this framework in analysing sentiments around different aspects of internet of things. We have tested this framework for 31 interrelated aspects in mobile domain and three possible sentiments (positive, negative and neutral).