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Decoding the Popularity of TV Series: A Network Analysis Perspective: Datasetby@kinetograph
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Decoding the Popularity of TV Series: A Network Analysis Perspective: Dataset

by Kinetograph: The Video Editing Technology Publication
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Kinetograph: The Video Editing Technology Publication

@kinetograph

The Kinetograph's the 1st motion-picture camera. At Kinetograph.Tech, we cover...

July 5th, 2024
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In this study, researchers attempt to understand the psychology behind TV ratings through character networks, and the different interactions between characters.
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Academic Research Paper

Academic Research Paper

Part of HackerNoon's growing list of open-source research papers, promoting free access to academic material.

Author:

(1) Melody Yu, Sage Hill School, California, USA.

DATASET

Our dataset is composed of character networks created by Bost. et. al. 2016 from three popular TV series. To capture a dynamic view of the character interactions, every episode’s character network is constructed by creating multiple successive static character networks.


A single-character network, also described as a segment graph or temporal graph, is defined as the interactions between characters over a period of ten scenes. Each episode contains multiple scenes, which means it can be split into multiple segment graphs. For the TV series Game of Thrones episode 1, 31 segment graphs are created from 310 scenes. Each graph of this episode contains between 14 and 17 nodes and 15 to 18 edges.


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Fig. 1. Game of Throne Season 1, Episode 1, S120-S130 Character Network.

Fig. 1. Game of Throne Season 1, Episode 1, S120-S130 Character Network.


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Our dataset is extracted from three popular TV series: Breaking Bad (seasons 1-2), Game of Thrones (seasons 1-5), and House of Cards (seasons 1-2).


We additionally use the reviews of these shows from IMDb, an online database of information related to films and television series. Each review shows the average rating of an episode, represented by a decimal number between 1 and 10 with higher numbers representing more favorable or more liked episodes. IMDb’s reviews are formed by aggregating individual reviews from registered users. Users are allowed to cast one vote per episode.


It is important to note that IMDb ratings for TV show episodes reflect the overall quality of the episode, not just the character interactions and plot. Other factors such as special effects, guest stars, and cinematography may also influence the score given by viewers. It is possible that these additional elements contribute to the overall enjoyment of the episode and are therefore included in the rating.


Figure 2 shows the IMDb reviews of Season 1 of Game of Thrones. The x-axis is the name of the episode, while the y-axis is the IMDb review of the episode.


Fig. 2. Game of Thrones Episode Review from IMDb.

Fig. 2. Game of Thrones Episode Review from IMDb.


This paper is available on arxiv under CC 4.0 license.


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