Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Is it feasible to detect FLOSS version release events from textual
  messages? A case study on Stack Overflow   Topic Detection and Tracking (TDT) is a very active research question within
the area of text mining, generally applied to news feeds and Twitter datasets,
where topics and events are detected. The notion of "event" is broad, but
typically it applies to occurrences that can be detected from a single post or
a message. Little attention has been drawn to what we call "micro-events",
which, due to their nature, cannot be detected from a single piece of textual
information. The study investigates the feasibility of micro-event detection on
textual data using a sample of messages from the Stack Overflow Q&A platform
and Free/Libre Open Source Software (FLOSS) version releases from Libraries.io
dataset. We build pipelines for detection of micro-events using three different
estimators whose parameters are optimized using a grid search approach. We
consider two feature spaces: LDA topic modeling with sentiment analysis, and
hSBM topics with sentiment analysis. The feature spaces are optimized using the
recursive feature elimination with cross validation (RFECV) strategy.
  In our experiments we investigate whether there is a characteristic change in
the topics distribution or sentiment features before or after micro-events take
place and we thoroughly evaluate the capacity of each variant of our analysis
pipeline to detect micro-events. Additionally, we perform a detailed
statistical analysis of the models, including influential cases, variance
inflation factors, validation of the linearity assumption, pseudo R squared
measures and no-information rate. Finally, in order to study limits of
micro-event detection, we design a method for generating micro-event synthetic
datasets with similar properties to the real-world data, and use them to
identify the micro-event detectability threshold for each of the evaluated
classifiers.

34
The categories of this paper are: chem-ph
22
The categories of this paper are: chao-dyn
32
The categories of this paper are: atom-ph
37
The categories of this paper are: supr-con
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph
14
The categories of this paper are: math-ph
2
The categories of this paper are: math
35
The categories of this paper are: mtrl-th
18
The categories of this paper are: econ
30
The categories of this paper are: q-alg
3
The categories of this paper are: physics
36
The categories of this paper are: cmp-lg
10
The categories of this paper are: q-bio
24
The categories of this paper are: dg-ga
27
The categories of this paper are: comp-gas