Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Lecture slides are also available online.

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Sentiment Analysis and Opinion Mining

The inherent nature of social media content poses serious challenges to practical applications of sentiment analysis. We present VADER, a simple rule-based model for general sentiment analysis, and compare its effectiveness to eleven typical state-of-practice benchmarks including LIWC, ANEW, the General Inquirer, SentiWordNet, and machine learning oriented techniques relying on Naive Bayes, Maximum Entropy, and Support Vector Machine (SVM) algorithms. Using a combination of qualitative and quantitative methods, we first construct and empirically validate a gold-standard list of lexical features (along with their associated sentiment intensity measures) which are specifically attuned to sentiment in microblog-like contexts. We then combine these lexical features with consideration for five general rules that embody grammatical and syntactical conventions for expressing and emphasizing sentiment intensity. Interestingly, using our parsimonious rule-based model to assess the sentiment of tweets, we find that VADER outperforms individual human raters (F1 Classification Accuracy = 0.96 and 0.84, respectively), and generalizes more favorably across contexts than any of our benchmarks.

/pdf/vader-a-parsimonious-rule-based-model-for-sentiment-analysis-47uwj744t2.pdf

VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text

行銷硏究 : Marketing research

This handbook looks to provide academics and students with a comprehensive and holistic understanding of the phenomenon of innovation. Innovation spans a number of fields within the social sciences and humanities: Management, Economics, Geography, Sociology, Politics, Psychology, and History. Consequently, the rapidly increasing body of literature on innovation is characterized by a multitude of perspectives based on, or cutting across, existing disciplines and specializations. Scholars of innovation can come from such diverse starting points that much of this literature can be missed, and so constructive dialogues missed. The editors of The Oxford Handbook of Innovation have carefully selected and designed twenty-one contributions from leading academic experts within their particular field, each focusing on a specific aspect of innovation. These have been organized into four main sections, the first of which looks at the creation of innovations, with particular focus on firms and networks. Section Two provides an account of the wider systematic setting influencing innovation and the role of institutions and organizations in this context. Section Three explores some of the diversity in the working of innovation over time and across different sectors of the economy, and Section Four focuses on the consequences of innovation with respect to economic growth, international competitiveness, and employment. An introductory overview, concluding remarks, and guide to further reading for each chapter, make this handbook a key introduction and vital reference work for researchers, academics, and advanced students of innovation. Contributors to this volume - Jan Fagerberg, University of Oslo William Lazonick, INSEAD Walter W. Powell, Stanford University Keith Pavitt, SPRU Alice Lam, Brunel University Keith Smith, INTECH Charles Edquist, Linkoping David Mowery, University of California, Berkeley Mary O'Sullivan, INSEAD Ove Granstrand, Chalmers Bjorn Asheim, University of Lund Rajneesh Narula, Copenhagen Business School Antonello Zanfei, Urbino Kristine Bruland, University of Oslo Franco Malerba, University of Bocconi Nick Von Tunzelmann, SPRU Ian Miles, University of Manchester Bronwyn Hall, University of California, Berkeley Bart Verspagen , ECIS Francisco Louca, ISEG Manuel M. Godinho, ISEG Richard R. Nelson, Mario Pianta, Urbino Bengt-Ake Lundvall, Aalborg

The Oxford Handbook of Innovation

/pdf/the-theory-of-industrial-organization-19bejph0ej.pdf

The Theory of Industrial Organization

In den Sozialwissenschaften werden Längsschnittstudien häufig angewendet, um sozialen und ökonomischen Wandel zu beschreiben und zu erklären. Das Potenzial von Längsschnittuntersuchungen liegt in der Analyse von Veränderungen, Entwicklungen, zeitlichen Prozessen oder Wandlungsvorgängen, wofür Daten für einen Zeitraum vorliegen müssen. Anwendungsmöglichkeiten sind auch in den Wirtschaftswissenschaften und der betriebswirtschaftlichen Forschung gegeben, allerdings wird diese Forschungsmethodik hier seltener angewendet. Dennoch besitzen Längsschnittanalysen ein außerordentliches Potenzial, weil sie anders als Querschnittsstudien wichtige Erkenntnisse über Dynamik, Veränderungen und Wandlungsprozesse liefern können und auch Aussagen über Kausalitäten zulassen (vgl. Dierkes, 1977, S. 113; Baltes/Nesselroade, 1979, S. 23–27; Hakim, 2000, S. 124 f.).

https://www.beck-elibrary.de/10.15358/0340-1650-2007-7-355.pdf

Methoden der Längsschnittanalyse in den Wirtschafts- und Sozialwissenschaften

The decision to syndicate investments in entrepreneurial finance has been explained through financial, networking, and resource-based perspectives. We posit that next to these three perspectives a ...

A personality perspective on business angel syndication

The paper uses data from the German Socio-Economic Panel Study (SOEP) to analyze start-ups by foreigners in Germany The regression results are the following: First, foreigners in self-employment are found to earn more than foreigners in a regular employment position Second, foreigners seem to gain more from self-employment relative to Germans The earnings increase from self-employment is larger for foreigners than it is for Germans The findings are discussed from a policy and an entrepreneurship education perspective We argue that there is a great potential for entrepreneurship education targeting foreigners

Unternehmensgründungen von Ausländern in Deutschland: Einkommenseffekte und Implikationen für die Gründungslehre

The paper uses data from the German Socio-Economic Panel (SOEP) to analyze entrepreneurial activities by foreigners in Germany. The results from our regression analysis are the following: First, foreigners in self-employment are found to earn more than foreigners in a regular employment position. Second, foreigners seem to gain more from self-employment compared to German entrepreneurs. Also, the earnings increase from self-employment is larger for foreigners than it is for Germans. The findings are discussed from a policy and an entrepreneurship education perspective.

Self-Employment by Foreigners in Germany: Income Effects and Implications for Entrepeneurship Support Policies

How does the social capital of venture capitalists (VCs) affect the funding of start-ups? Extant entrepreneurship literature conceptualizes a substitute effect between the social and financial capital that new firms attain from their investors. On the contrary, by building on the rich social capital literature, we hypothesize a positive effect of VCs’ social capital, derived from past syndication, on the amount of money that start-ups receive. Specifically, we argue that both structural aspects of VCs’ social network, such as the number of connections and the spanning of structural holes, and relational aspects, such as the diversity of network partners’ attributes, provide VCs with superior access to information about current investment objects and opportunities to leverage them in the future, increasing their willingness to invest in these firms. Our empirical results, derived from a novel dataset containing more than 5,000 funding rounds in the Internet and IT sector, strongly confirm our hypotheses. Both structural and relational attributes of VCs’ syndication networks have a significant influence on the funds received by start-up firms, highlighting the importance of a social capital perspective on new venture funding. We discuss the implications of our findings for theories of venture capital and entrepreneurship, showing that the role and effect of VCs’ social capital on start-up firms is much more complex than previously argued in the literature.

https://papers.ssrn.com/sol3/Delivery.cfm/20274.pdf?abstractid=1657794&mirid=5

Philipp Sandner

Papers

Methoden der Längsschnittanalyse in den Wirtschafts- und Sozialwissenschaften

A personality perspective on business angel syndication

Unternehmensgründungen von Ausländern in Deutschland: Einkommenseffekte und Implikationen für die Gründungslehre

Self-Employment by Foreigners in Germany: Income Effects and Implications for Entrepeneurship Support Policies

The Social Capital of Venture Capitalists and its Impact on the Funding of Start-Up Firms