Title | ||
---|---|---|
In Quest of Significance: Identifying Types of Twitter Sentiment Events that Predict Spikes in Sales |
Abstract | ||
---|---|---|
We study the power of Twitter events to predict consumer
sales events by analysing sales for 75 companies from the retail sector
and over 150 million tweets mentioning those companies along with their
sentiment. We suggest an approach for events identification on Twitter
extending existing methodologies of event study. We also propose a robust
method for clustering Twitter events into different types based on
their shape, which captures the varying dynamics of information propagation
through the social network. We provide empirical evidence that
through events differentiation based on their shape we can clearly identify
types of Twitter events that have a more significant power to predict
spikes in sales than the aggregated Twitter signal. |
Year | Venue | Field |
---|---|---|
2015 | CoRR | Data mining,Social network,Empirical evidence,Computer science,Information propagation,Cluster analysis,Event study |
DocType | Volume | Citations |
Journal | abs/1508.03981 | 1 |
PageRank | References | Authors |
0.36 | 16 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
olga kolchyna | 1 | 5 | 0.76 |
tharsis t p souza | 2 | 5 | 0.76 |
Tomaso Aste | 3 | 57 | 11.62 |
Philip C. Treleaven | 4 | 419 | 125.14 |