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Auflistung nach Schlagwort "Social media"

1 - 9 von 9
  • Zeitschriftenartikel
    Informationssysteme für „Wicked Problems“
    (Wirtschaftsinformatik: Vol. 56, No. 1, 2014) Schoder, Detlef; Putzke, Johannes; Metaxas, Panagiotis Takis; Gloor, Peter A.; Fischbach, Kai
    Mit unserem Forschungskommentar zeigen wir vielversprechende Forschungsrichtungen auf, die aus dem wechselseitigen Zusammenspiel von Social Media und Collective Intelligence hervorgehen. Wir konzentrieren uns auf sogenannte „Wicked Problems“ – eine Klasse von Problemen, „for which no single computational formulation of the problem is sufficient, for which different stakeholders do not even agree on what the problem really is, and for which there are no right or wrong answers, only answers that are better or worse from different points of view“ (Introne et al. in Künstl. Intell. 27:45–52, 2013). Wir argumentieren, dass insbesondere die Disziplin Wirtschaftsinformatik einen Beitrag zur Gestaltung geeigneter Systeme leisten kann und zwar aufgrund des Nutzens, der sich aus einer kombinierten Perspektive von Social Media und Collective Intelligence ableitet. Wir legen die Relevanz und Aktualität von Social Media und Collective Intelligence für die Wirtschaftsinformatik dar, schlagen erforderliche Funktionalitäten von Informationssystemen für Wicked Problems vor, beschreiben verwandte Themenfelder und Herausforderungen für die Forschung, identifizieren wissenschaftliche Methoden zu ihrer Lösung und führen konkrete Beispiele für erste Forschungsergebnisse an.AbstractThe objective of this commentary is to propose fruitful research directions built upon the reciprocal interplay of social media and collective intelligence. We focus on „wicked problems“ – a class of problems that Introne et al. (Künstl. Intell. 27:45–52, 2013) call „problems for which no single computational formulation of the problem is sufficient, for which different stakeholders do not even agree on what the problem really is, and for which there are no right or wrong answers, only answers that are better or worse from different points of view“. We argue that information systems research in particular can aid in designing appropriate systems due to benefits derived from the combined perspectives of both social media and collective intelligence. We document the relevance and timeliness of social media and collective intelligence for business and information systems engineering, pinpoint needed functionality of information systems for wicked problems, describe related research challenges, highlight prospective suitable methods to tackle those challenges, and review examples of initial results.
  • Zeitschriftenartikel
    Informationsunschärfe in Big Data
    (Wirtschaftsinformatik: Vol. 56, No. 5, 2014) Bendler, Johannes; Wagner, Sebastian; Brandt, Tobias; Neumann, Dirk
    Während die klassische Definition von Big Data ursprünglich nur die drei Größen Datenmenge (Volume), Datenrate (Velocity) und Datenvielfalt (Variety) umfasste, ist in jüngster Zeit der Wahrheitsgehalt (Veracity) als weitere Dimension mehr und mehr in den wissenschaftlichen und praktischen Fokus gerückt. Der noch immer wachsende Bereich der Sozialen Medien und damit verbundene benutzergenerierte Datenmengen verlangen nach neuen Methoden, die die enthaltene Datenunschärfe abschätzen und kontrollieren können. Dieser Beitrag widmet sich einem Aspekt der Datenunschärfe und stellt einen neuartigen Ansatz vor, der die Verlässlichkeit von benutzergenerierten Daten auf Basis von wiederkehrenden Mustern abschätzt. Zu diesem Zweck wird eine große Menge von Twitter-Statusnachrichten mit geographischer Standortinformation aus San Francisco untersucht und mit Points of Interest (POIs), wie beispielsweise Bars, Restaurants oder Parks, in Verbindung gebracht. Das vorgeschlagene Modell wird durch kausale Beziehungen zwischen Points of Interest und den in der Umgebung vorliegenden Twitter-Meldungen validiert. Weiterhin wird die zeitliche Dimension dieser Beziehung in Betracht gezogen, um so in Abhängigkeit der Art des POI wiederkehrende Muster zu identifizieren. Die durchgeführten Analysen münden in einem Indikator, der die Verlässlichkeit von vorliegenden Daten in räumlicher und zeitlicher Dimension abschätzt.AbstractWhile the classic definition of Big Data included the dimensions volume, velocity, and variety, a fourth dimension, veracity, has recently come to the attention of researchers and practitioners. The increasing amount of user-generated data associated with the rise of social media emphasizes the need for methods to deal with the uncertainty inherent to these data sources. In this paper we address one aspect of uncertainty by developing a new methodology to establish the reliability of user-generated data based upon causal links with recurring patterns. We associate a large data set of geo-tagged Twitter messages in San Francisco with points of interest, such as bars, restaurants, or museums, within the city. This model is validated by causal relationships between a point of interest and the amount of messages in its vicinity. We subsequently analyze the behavior of these messages over time using a jackknifing procedure to identify categories of points of interest that exhibit consistent patterns over time. Ultimately, we condense this analysis into an indicator that gives evidence on the certainty of a data set based on these causal relationships and recurring patterns in temporal and spatial dimensions.
  • Konferenzbeitrag
    IT for Peace? Fighting Against Terrorism in Social Media – An Explorative Twitter Study
    (i-com: Vol. 16, No. 2, 2017) Reuter, Christian; Pätsch, Katja; Runft, Elena
    The Internet and especially social media are not only used for supposedly good purposes. For example, the recruitment of new members and the dissemination of ideologies of terrorism also takes place in the media. However, the fight against terrorism also makes use of the same tools. The type of these countermeasures, as well as the methods, are covered in this work. In the first part, the state of the art is summarized. The second part presents an explorative empirical study of the fight against terrorism in social media, especially on Twitter. Different, preferably characteristic forms are structured within the scope with the example of Twitter. The aim of this work is to approach this highly relevant subject with the goal of peace, safety and safety from the perspective of information systems. Moreover, it should serve following researches in this field as basis and starting point.
  • Zeitschriftenartikel
    Learning to Discover Political Activism in the Twitterverse
    (KI - Künstliche Intelligenz: Vol. 27, No. 1, 2013) Finn, Samantha; Mustafaraj, Eni
    When analysing social media conversations, in search of the public opinion about an unfolding political event that is being discussed in real-time (e.g., presidential debates, major speeches, etc.), it is important to distinguish between two groups of participants: political activists and the general public. To address this problem, we propose a supervised machine-learning approach, which uses inexpensively acquired labeled data from mono-thematic Twitter accounts to learn a binary classifier for the labels “political activist” and “general public”. While the classifier has a 92 % accuracy on individual tweets, when applied to the last 200 tweets from accounts of a set of 1000 Twitter users, it classifies accounts with a 97 % accuracy. Our work demonstrates that machine learning algorithms can play a critical role in improving the quality of social media analytics and understanding, whose importance is increasing as social media adoption becomes widespread.
  • Zeitschriftenartikel
    Meinungsäußerung und -bildung in sozialen Medien
    (Wirtschaftsinformatik: Vol. 54, No. 3, 2012) Agarwal, Nitin; Lim, Merlyna; Wigand, Rolf
    Neu aufkommende cybersoziale Bewegungen (CSM) haben öfter Schlagzeilen in den Nachrichten gemacht. Trotz ihrer Popularität fehlt eine systematische Methodenlehre, um diese Bewegungen empirisch in komplexen Onlineumgebungen zu untersuchen. Mit Hilfe der Onlinekampagne von Al-Huwaider als Fallbeispiel versucht dieser Beitrag, eine klare und grundlegende Analyse zu etablieren, um CSM zu erläutern. Wir trugen 150 Blogs aus 17 Ländern im Zeitraum zwischen April 2003 und Juli 2010 mit spezieller Ausrichtung auf die Al-Huwaider-Kampagne zusammen, um die multikulturellen Aspekte für unsere Analyse zu erfassen. Die Analyse stützt sich auf die drei zentralen Pfeiler individueller, communitybezogener und übernationaler Sicht und entwickelt neue Algorithmen für CSM-Modelle unter Benutzung existierender Theorien zu Kollektivaktionen und quantitativer Analysen sozialer Netzwerke. Der Beitrag liefert eine Methodik zur Untersuchung der Verbreitung von Themen in sozialen Netzwerken und prüft die Rolle einflussreicher Mitglieder der Community. Die vorgeschlagene Methodik liefert ein funktionelles Hilfsmittel, um die Komplexität und die Dynamik von CSM zu verstehen. Eine solche Methodik unterstützt uns auch in der Beobachtung des Vorübergehens von CSM mit der zukünftigen Möglichkeit, übernationale Reichweiten darzustellen. Die Studie spricht das Fehlen von grundlegenden Untersuchungen zur Entstehung von CSM an. Der Beitrag hat Bedeutung für die Wirtschaft, Marketing und weitere Bereiche über das hier als Darstellung gewählte Beispiel hinaus.AbstractEmerging cyber-collective social movements (CSMs) have frequently made headlines in the news. Despite their popularity, there is a lack of systematic methodologies to empirically study such movements in complex online environments. Using the Al-Huwaider online campaign as a case to illustrate our methodology, this contribution attempts to establish a rigorous and fundamental analysis that explains CSMs. We collected 150 blogs from 17 countries ranging between April 2003 and July 2010 with a special focus on Al-Huwaider’s campaigns capturing multi-cultural aspects for our analysis. Bearing the analysis upon three central tenets of individual, community, and transnational perspectives, we develop novel algorithms modeling CSMs by utilizing existing collective action theories and computational social network analysis. This article contributes a methodology to study the diffusion of issues in social networks and examines roles of influential community members. The proposed methodology provides a rigorous tool to understand the complexity and dynamics of CSMs. Such methodology also assists us in observing the transcending nature of CSMs with future possibilities for modeling transnational outreach. Our study addresses the lack of fundamental research on the formation of CSMs. This research contributes novel methodologies that can be applied to many settings including business, marketing and many others, beyond the exemplary setting chosen here for illustrative purposes.
  • Zeitschriftenartikel
    Reflecting on Social Media Behavior by Structuring and Exploring Posts and Comments
    (i-com: Vol. 19, No. 3, 2021) Herder, Eelco; Roßner, Daniel; Atzenbeck, Claus
    Social networks use several user interaction techniques for enabling and soliciting user responses, such as posts, likes and comments. Some of these triggers may lead to posts or comments that a user may regret at a later stage. In this article, we investigate how users may be supported in reflecting upon their past activities, making use of an exploratory spatial hypertext tool. We discuss how we transform raw Facebook data dumps into a graph-based structure and reflect upon design decisions. First results provide insights in users motivations for using such a tool and confirm that the approach helps them in discovering past activities that they perceive as outdated or even embarrassing.
  • Zeitschriftenartikel
    Social Media Analytics: Wie die Ausrichtung an den Unternehmenszielen gelingt
    (HMD Praxis der Wirtschaftsinformatik: Vol. 53, No. 5, 2016) Kleindienst, Dominikus
    In sozialen Medien wie z. B. Facebook oder Twitter existieren große Mengen an bisher teils ungenutzten, geschäftsrelevanten Daten. Die meisten Unternehmen haben dies erkannt und wenden verschiedene Ansätze aus dem Bereich der Social Media Analytics (SMA) an, um derartige Daten zu identifizieren und für ihr Geschäftsmodell nutzbar zu machen. Entgegen dem ihr beigemessenen hohen Stellenwert wird die Steuerung von SMA jedoch häufig den IT-Abteilungen überlassen, welche die Anwendung von SMA nicht immer ausreichend an den Unternehmenszielen ausrichten, sondern sich zu sehr auf rein technische Fragestellungen der SMA-Implementierung fokussieren. Dies führt dazu, dass eher auf eine effiziente Datensammlung und -speicherung abgezielt wird, als darauf, welche Daten benötigt und wie diese im Sinne des Geschäftsmodells verwendet werden. Konkrete Handlungsempfehlungen dafür, wie die Ausrichtung von SMA an den Unternehmenszielen gelingen kann, gibt es bisher nicht. Dieser Beitrag stellt deshalb ein existierendes Framework vor, mit dessen Hilfe die Ausrichtung der SMA an den Unternehmenszielen gelingen soll. Ziel des Beitrages ist es insbesondere, die Anwendung des Frameworks in der Praxis zu erleichtern. Zu diesem Zweck wird das Framework in Hinblick auf seine Einsetzbarkeit in der Praxis angepasst, ein anschauliches Fallbeispiel aufgezeigt sowie eine Evaluation des Ansatzes in Experteninterviews durchgeführt.AbstractLarge amounts of unused, business-relevant data exist in social media such as Facebook or Twitter. Most companies have realized this potential and apply different approaches from the area of social media analytics (SMA) in order to identify data that are useful for their business models. Although SMA are already considered to be important, management often hands off the responsibility to IT departments, who do not always sufficiently align their efforts with the business objectives, but focus too much on technical challenges. Hence, they rather aim at efficient data collection and storage instead of business alignment. As there are no concrete recommendations to practitioners on how to align SMA with business objectives yet, this paper presents an existing framework that helps with SMA business alignment. This paper particularly aims at simplifying the framework’s application in practice. Accordingly, the framework is adapted for practical use, an illustrative case is presented, and the approach is evaluated by expert interviews.
  • Zeitschriftenartikel
    Towards a Conceptualization of Data and Information Quality in Social Information Systems
    (Business & Information Systems Engineering: Vol. 59, No. 1, 2017) Tilly, Roman; Posegga, Oliver; Fischbach, Kai; Schoder, Detlef
    Data and information quality (DIQ) have been defined traditionally in an organizational context and with respect to traditional information systems (IS). Numerous frameworks have been developed to operationalize traditional DIQ accordingly. However, over the last decade, social information systems (SocIS) such as social media have emerged that enable social interaction and open collaboration of voluntary prosumers, rather than supporting specific tasks as do traditional IS in organizations. Based on a systematic literature review, the paper identifies and categorizes prevalent DIQ conceptualizations. The authors differentiate the various understandings of DIQ in light of the unique characteristics of SocIS and conclude that they do not capture DIQ in SocIS well, nor how it is defined, maintained, and improved through social interaction. The paper proposes a new conceptualization of DIQ in SocIS that can explain the interplay of existing conceptualizations and provides the foundation for future research on DIQ in SocIS.
  • Zeitschriftenartikel
    Using Twitter to Predict the Stock Market
    (Business & Information Systems Engineering: Vol. 57, No. 4, 2015) Nofer, Michael; Hinz, Oliver
    Behavioral finance researchers have shown that the stock market can be driven by emotions of market participants. In a number of recent studies mood levels have been extracted from Social Media applications in order to predict stock returns. The paper tries to replicate these findings by measuring the mood states on Twitter. The sample consists of roughly 100 million tweets that were published in Germany between January, 2011 and November, 2013. In a first analysis, a significant relationship between aggregate Twitter mood states and the stock market is not found. However, further analyses also consider mood contagion by integrating the number of Twitter followers into the analysis. The results show that it is necessary to take into account the spread of mood states among Internet users. Based on the results in the training period, a trading strategy for the German stock market is created. The portfolio increases by up to 36 % within a six-month period after the consideration of transaction costs.