12: Webpage

Summarizing Data by Authors

This code snippet identifies missing values in the dataset and summarizes the distribution of publications by authors. It visualizes the results using a Plotly bar graph.

Analyzing Temporal Trends in Article Publications

This code converts the ‘DATE’ column to datetime format and groups the data by date to count the number of articles. It then plots these counts over time using a line graph to reveal trends.

Unigrams

Bigrams

Trigrams

Quadgrams

Histogram of Word Counts

This code segment loads text data, calculates word and character counts, and visualizes the distribution of word counts across documents. The histogram of word counts allows us to assess the verbosity or conciseness of the entries in the dataset.

Histogram of Character Counts

This code generates a histogram to visualize the distribution of character counts in the dataset. The visualization helps identify the common length of entries and any outliers, using a clear and concise histogram format.

Visualization of POS Tag Frequencies

This script loads textual data, utilizes the NLTK library to extract and count Part-of-Speech tags, and generates histograms for each POS tag type to analyze their frequencies. The visualizations offer insights into the linguistic structure of the texts.

[nltk_data] Downloading package averaged_perceptron_tagger to
[nltk_data]     C:\Users\srinivas\AppData\Roaming\nltk_data...
[nltk_data]   Package averaged_perceptron_tagger is already up-to-
[nltk_data]       date!
[nltk_data] Downloading package punkt to
[nltk_data]     C:\Users\srinivas\AppData\Roaming\nltk_data...
[nltk_data]   Package punkt is already up-to-date!
[nltk_data] Downloading package universal_tagset to
[nltk_data]     C:\Users\srinivas\AppData\Roaming\nltk_data...
[nltk_data]   Package universal_tagset is already up-to-date!

Normal Distribution to Title Lengths

This code calculates the normal distribution based on title lengths and overlays this distribution on a histogram of actual title lengths. This visualization helps assess the normality of title length distribution in the dataset.

Advanced ML Analytics

Topic Modeling

(0, '0.022*"leav" + 0.021*"forc" + 0.020*"william" + 0.020*"wife" + 0.020*"appeal"')
(1, '0.032*"joe" + 0.031*"giudic" + 0.029*"cheat" + 0.029*"christian" + 0.017*"pollster"')
(2, '0.150*"thehil" + 0.060*"trump" + 0.017*"report" + 0.014*"dem" + 0.012*"gop"')
(3, '0.027*"win" + 0.021*"return" + 0.020*"season" + 0.019*"past" + 0.018*"bring"')
(4, '0.045*"new" + 0.034*"deni" + 0.031*"chef" + 0.030*"kitchen" + 0.026*"star"')
C:\Users\srinivas\AppData\Roaming\Python\Python38\site-packages\pyLDAvis\_prepare.py:243: FutureWarning:

In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only

Emotion Recognition and Sentiment Analysis

C:\Users\srinivas\AppData\Roaming\Python\Python38\site-packages\plotly\io\_renderers.py:396: DeprecationWarning:

distutils Version classes are deprecated. Use packaging.version instead.

C:\Users\srinivas\AppData\Roaming\Python\Python38\site-packages\plotly\io\_renderers.py:396: DeprecationWarning:

distutils Version classes are deprecated. Use packaging.version instead.
C:\Users\srinivas\AppData\Roaming\Python\Python38\site-packages\plotly\io\_renderers.py:396: DeprecationWarning:

distutils Version classes are deprecated. Use packaging.version instead.

C:\Users\srinivas\AppData\Roaming\Python\Python38\site-packages\plotly\io\_renderers.py:396: DeprecationWarning:

distutils Version classes are deprecated. Use packaging.version instead.
C:\Users\srinivas\AppData\Roaming\Python\Python38\site-packages\plotly\io\_renderers.py:396: DeprecationWarning:

distutils Version classes are deprecated. Use packaging.version instead.

C:\Users\srinivas\AppData\Roaming\Python\Python38\site-packages\plotly\io\_renderers.py:396: DeprecationWarning:

distutils Version classes are deprecated. Use packaging.version instead.
C:\Users\srinivas\AppData\Roaming\Python\Python38\site-packages\plotly\io\_renderers.py:396: DeprecationWarning:

distutils Version classes are deprecated. Use packaging.version instead.

C:\Users\srinivas\AppData\Roaming\Python\Python38\site-packages\plotly\io\_renderers.py:396: DeprecationWarning:

distutils Version classes are deprecated. Use packaging.version instead.
C:\Users\srinivas\AppData\Roaming\Python\Python38\site-packages\plotly\io\_renderers.py:396: DeprecationWarning:

distutils Version classes are deprecated. Use packaging.version instead.

C:\Users\srinivas\AppData\Roaming\Python\Python38\site-packages\plotly\io\_renderers.py:396: DeprecationWarning:

distutils Version classes are deprecated. Use packaging.version instead.
C:\Users\srinivas\AppData\Roaming\Python\Python38\site-packages\plotly\io\_renderers.py:396: DeprecationWarning:

distutils Version classes are deprecated. Use packaging.version instead.

C:\Users\srinivas\AppData\Roaming\Python\Python38\site-packages\plotly\io\_renderers.py:396: DeprecationWarning:

distutils Version classes are deprecated. Use packaging.version instead.

Word Cloud For All Headlines

Frequently Occuring Words in all News Headlines

Word Cloud For Positive Headlines

Frequently Occuring Words in positive sentiment News Headlines

Word Cloud For Negative Headlines

Frequently Occuring Words in negative sentiment News Headlines

Word Cloud For Neutral Headlines

Frequently Occuring Words in neutral sentiment News Headlines

Deep Learning Classifier

Model Plot

Model Plot

Model Loss

Model Training and Validation Loss

Model Accuracy

Model Training and Validation Accuracy

Prediction Matrix

Model Training and Validation Accuracy