Social Media Influencers in Strategic Communication
نویسندگان
چکیده
منابع مشابه
Identifying Influencers in Social Networks
The central idea in designing various marketing strategies for online social networks is to identify the influencers in the network. The influential individuals induce “word-of-mouth” effects in the network. These individuals are responsible for triggering long cascades of influence that convince their peers to perform a similar action (buying a product, for instance). Targeting these influenti...
متن کاملCompeting for Influencers in a Social Network
This paper studies the competition between firms for influencers in a network. Firms spend effort to convince influencers to recommend their products. The analysis identifies the offensive and defensive roles of spending on influencers. The value of an influencer only depends on the in-degree distribution of the influence network. Influencers who exclusively cover a high number of consumers are...
متن کاملPredict Influencers in the Social Network
Given two persons and their social network features, our job is to predict which one is more influential. In our project, we collect training samples from Kaggle based on human judgement. We use several different models to make predictions, such as Logistic Regression, SVM, Naive Bayes and Neural Network. We also use some auxiliary techniques like cross validation, feature selection and data pr...
متن کاملSocial Media for Success: a Strategic Framework
Social media is a phenomenon widely used by companies. Studies report that up to 94% of companies that have a marketing department make use of social media. Which social media platforms to adopt and how to use them to support the business strategies is often not a deliberate choice in companies. Therefore a strategic framework is proposed here that guides companies in making the choices that to...
متن کاملCollective Influence Algorithm to find influencers via optimal percolation in massively large social media
We elaborate on a linear-time implementation of Collective-Influence (CI) algorithm introduced by Morone, Makse, Nature 524, 65 (2015) to find the minimal set of influencers in networks via optimal percolation. The computational complexity of CI is O(N log N) when removing nodes one-by-one, made possible through an appropriate data structure to process CI. We introduce two Belief-Propagation (B...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Strategic Communication
سال: 2019
ISSN: 1553-118X,1553-1198
DOI: 10.1080/1553118x.2019.1634075