#GreenChemicals_2021-02-22_19-07-56.xlsx (experimental version)

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From:

NodeXLExcelAutomator

Uploaded on:

February 23, 2021

Short Description:

#GreenChemicals via NodeXL https://bit.ly/3buTwUG

@chemicalupdates

@hydrogenfsummit

@h2gazette

@archromagroup

@chemicalsgreen

@ecochemindia

@huntsman_corp

@covestro

@energyestate

@diccorporation

Top hashtags:

#greenchemicals

#ecofriendly

#ecochem

#hydrogen

#metinfo

Tweet
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@chemicalupdates

@hydrogenfsummit

@h2gazette

@archromagroup

@chemicalsgreen

@ecochemindia

@huntsman_corp

@covestro

@energyestate

@diccorporation

Top hashtags:

#greenchemicals

#ecofriendly

#ecochem

#hydrogen

#metinfo

Tweet

Description:

The graph represents a network of 11 Twitter users whose tweets in the requested range contained "#GreenChemicals", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Tuesday, 23 February 2021 at 03:07 UTC.

The requested start date was Tuesday, 23 February 2021 at 01:01 UTC and the maximum number of days (going backward) was 14.

The maximum number of tweets collected was 7,500.

The tweets in the network were tweeted over the 9-day, 7-hour, 55-minute period from Wednesday, 10 February 2021 at 07:06 UTC to Friday, 19 February 2021 at 15:01 UTC.

Additional tweets that were mentioned in this data set were also collected from prior time periods. These tweets may expand the complete time period of the data.

There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, and a self-loop edge for each tweet that is not a "replies-to" or "mentions".

The graph is directed.

The graph's vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.

The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.

The requested start date was Tuesday, 23 February 2021 at 01:01 UTC and the maximum number of days (going backward) was 14.

The maximum number of tweets collected was 7,500.

The tweets in the network were tweeted over the 9-day, 7-hour, 55-minute period from Wednesday, 10 February 2021 at 07:06 UTC to Friday, 19 February 2021 at 15:01 UTC.

Additional tweets that were mentioned in this data set were also collected from prior time periods. These tweets may expand the complete time period of the data.

There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, and a self-loop edge for each tweet that is not a "replies-to" or "mentions".

The graph is directed.

The graph's vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.

The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.

Vertices : 11

Unique Edges : 6

Edges With Duplicates : 9

Total Edges : 15

Number of Edge Types : 4

Tweet : 7

Retweet : 1

MentionsInRetweet : 1

Mentions : 6

Self-Loops : 7

Reciprocated Vertex Pair Ratio : 0

Reciprocated Edge Ratio : 0

Connected Components : 4

Single-Vertex Connected Components : 2

Maximum Vertices in a Connected Component : 6

Maximum Edges in a Connected Component : 5

Maximum Geodesic Distance (Diameter) : 2

Average Geodesic Distance : 1.234043

Graph Density : 0.0636363636363636

Modularity : 0.4

NodeXL Version : 1.0.1.443

Data Import : The graph represents a network of 11 Twitter users whose tweets in the requested range contained "#GreenChemicals", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Tuesday, 23 February 2021 at 03:07 UTC.

The requested start date was Tuesday, 23 February 2021 at 01:01 UTC and the maximum number of days (going backward) was 14.

The maximum number of tweets collected was 7,500.

The tweets in the network were tweeted over the 9-day, 7-hour, 55-minute period from Wednesday, 10 February 2021 at 07:06 UTC to Friday, 19 February 2021 at 15:01 UTC.

Additional tweets that were mentioned in this data set were also collected from prior time periods. These tweets may expand the complete time period of the data.

There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, and a self-loop edge for each tweet that is not a "replies-to" or "mentions".

Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.

Graph Source : GraphServerTwitterSearch

Graph Term : #GreenChemicals

Groups : The graph's vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.

Edge Color : Edge Weight

Edge Width : Edge Weight

Edge Alpha : Edge Weight

Vertex Radius : Betweenness Centrality

Unique Edges : 6

Edges With Duplicates : 9

Total Edges : 15

Number of Edge Types : 4

Tweet : 7

Retweet : 1

MentionsInRetweet : 1

Mentions : 6

Self-Loops : 7

Reciprocated Vertex Pair Ratio : 0

Reciprocated Edge Ratio : 0

Connected Components : 4

Single-Vertex Connected Components : 2

Maximum Vertices in a Connected Component : 6

Maximum Edges in a Connected Component : 5

Maximum Geodesic Distance (Diameter) : 2

Average Geodesic Distance : 1.234043

Graph Density : 0.0636363636363636

Modularity : 0.4

NodeXL Version : 1.0.1.443

Data Import : The graph represents a network of 11 Twitter users whose tweets in the requested range contained "#GreenChemicals", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Tuesday, 23 February 2021 at 03:07 UTC.

The requested start date was Tuesday, 23 February 2021 at 01:01 UTC and the maximum number of days (going backward) was 14.

The maximum number of tweets collected was 7,500.

The tweets in the network were tweeted over the 9-day, 7-hour, 55-minute period from Wednesday, 10 February 2021 at 07:06 UTC to Friday, 19 February 2021 at 15:01 UTC.

Additional tweets that were mentioned in this data set were also collected from prior time periods. These tweets may expand the complete time period of the data.

There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, and a self-loop edge for each tweet that is not a "replies-to" or "mentions".

Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.

Graph Source : GraphServerTwitterSearch

Graph Term : #GreenChemicals

Groups : The graph's vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.

Edge Color : Edge Weight

Edge Width : Edge Weight

Edge Alpha : Edge Weight

Vertex Radius : Betweenness Centrality

@chemicalupdates | |

Follow |

@hydrogenfsummit | |

Follow |

@h2gazette | |

Follow |

@archromagroup | |

Follow |

@chemicalsgreen | |

Follow |

@ecochemindia | |

Follow |

@huntsman_corp | |

Follow |

@covestro | |

Follow |

@energyestate | |

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@diccorporation | |

Follow |

Top URLs in Tweet in Entire Graph:

[1] https://www.fortunebusinessinsights.com/textile-chemicals-market-103284

Top URLs in Tweet in G1:

[1] https://www.fortunebusinessinsights.com/textile-chemicals-market-103284

[1] https://www.fortunebusinessinsights.com/textile-chemicals-market-103284

Top URLs in Tweet in G1:

[1] https://www.fortunebusinessinsights.com/textile-chemicals-market-103284

Top Domains in Tweet in Entire Graph:

[1] fortunebusinessinsights.com

Top Domains in Tweet in G1:

[1] fortunebusinessinsights.com

[1] fortunebusinessinsights.com

Top Domains in Tweet in G1:

[1] fortunebusinessinsights.com

Top Hashtags in Tweet in Entire Graph:

[9] greenchemicals

[3] ecofriendly

[3] ecochem

[3] hydrogen

[2] metinfo

[2] metalcleaning

[2] apachydrogensummit

[2] decarbonising

[1] geotreat

[1] geoinfo

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Top Hashtags in Tweet in G1:

[1] textilechemicals

[1] randd

[1] greenchemicals

Top Hashtags in Tweet in G2:

[3] hydrogen

[2] apachydrogensummit

[2] decarbonising

[1] greenchemicals

[1] renewableenergy

Top Hashtags in Tweet in G3:

[7] greenchemicals

[3] ecofriendly

[3] ecochem

[2] metalcleaning

[2] metinfo

[1] marblecleaning

[1] rustremoval

[1] geotreat

[1] geoinfo

[1] gcsözlük

[9] greenchemicals

[3] ecofriendly

[3] ecochem

[3] hydrogen

[2] metinfo

[2] metalcleaning

[2] apachydrogensummit

[2] decarbonising

[1] geotreat

[1] geoinfo

Tweet

Top Hashtags in Tweet in G1:

[1] textilechemicals

[1] randd

[1] greenchemicals

Top Hashtags in Tweet in G2:

[3] hydrogen

[2] apachydrogensummit

[2] decarbonising

[1] greenchemicals

[1] renewableenergy

Top Hashtags in Tweet in G3:

[7] greenchemicals

[3] ecofriendly

[3] ecochem

[2] metalcleaning

[2] metinfo

[1] marblecleaning

[1] rustremoval

[1] geotreat

[1] geoinfo

[1] gcsözlük

Top Words in Tweet in Entire Graph:

[9] #greenchemicals

[4] eco

[3] marble

[3] industrial

[3] #ecofriendly

[3] #ecochem

[2] termal

[2] için

[2] metal

[2] ve

Top Words in Tweet in G1:

[2] market

Top Words in Tweet in G2:

[2] #apachydrogensummit

[2] #hydrogen's

[2] role

[2] #decarbonising

[2] industrial

[2] processes

[2] energy

[2] supply

[2] heavy

Top Words in Tweet in G3:

[7] #greenchemicals

[4] eco

[3] marble

[3] #ecofriendly

[3] #ecochem

[2] green

[2] cleaning

[2] stains

[2] rust

[2] #metalcleaning

[9] #greenchemicals

[4] eco

[3] marble

[3] industrial

[3] #ecofriendly

[3] #ecochem

[2] termal

[2] için

[2] metal

[2] ve

Top Words in Tweet in G1:

[2] market

Top Words in Tweet in G2:

[2] #apachydrogensummit

[2] #hydrogen's

[2] role

[2] #decarbonising

[2] industrial

[2] processes

[2] energy

[2] supply

[2] heavy

Top Words in Tweet in G3:

[7] #greenchemicals

[4] eco

[3] marble

[3] #ecofriendly

[3] #ecochem

[2] green

[2] cleaning

[2] stains

[2] rust

[2] #metalcleaning

Top Word Pairs in Tweet in Entire Graph:

[3] #ecofriendly,#greenchemicals

[2] #metinfo,#greenchemicals

[2] eco,green

[2] #greenchemicals,#ecochem

[2] #metalcleaning,#ecofriendly

[2] #apachydrogensummit,#hydrogen's

[2] #hydrogen's,role

[2] role,#decarbonising

[2] #decarbonising,industrial

[2] industrial,processes

Top Word Pairs in Tweet in G2:

[2] #apachydrogensummit,#hydrogen's

[2] #hydrogen's,role

[2] role,#decarbonising

[2] #decarbonising,industrial

[2] industrial,processes

[2] processes,energy

[2] energy,supply

[2] supply,heavy

Top Word Pairs in Tweet in G3:

[3] #ecofriendly,#greenchemicals

[2] eco,green

[2] #greenchemicals,#ecochem

[2] #metalcleaning,#ecofriendly

[2] #metinfo,#greenchemicals

[3] #ecofriendly,#greenchemicals

[2] #metinfo,#greenchemicals

[2] eco,green

[2] #greenchemicals,#ecochem

[2] #metalcleaning,#ecofriendly

[2] #apachydrogensummit,#hydrogen's

[2] #hydrogen's,role

[2] role,#decarbonising

[2] #decarbonising,industrial

[2] industrial,processes

Top Word Pairs in Tweet in G2:

[2] #apachydrogensummit,#hydrogen's

[2] #hydrogen's,role

[2] role,#decarbonising

[2] #decarbonising,industrial

[2] industrial,processes

[2] processes,energy

[2] energy,supply

[2] supply,heavy

Top Word Pairs in Tweet in G3:

[3] #ecofriendly,#greenchemicals

[2] eco,green

[2] #greenchemicals,#ecochem

[2] #metalcleaning,#ecofriendly

[2] #metinfo,#greenchemicals

Top Mentioned in Entire Graph:

Top Mentioned in G1:

Top Mentioned in G2:

@hydrogenfsummit | ||

@archromagroup | ||

@huntsman_corp | ||

@diccorporation | ||

@kiri_industries | ||

@covestro | ||

@energyestate | ||

Top Mentioned in G1:

@archromagroup | ||

@huntsman_corp | ||

@diccorporation | ||

@kiri_industries | ||

@covestro | ||

Top Mentioned in G2:

@hydrogenfsummit | ||

@energyestate | ||

Top Tweeters in Entire Graph:

Top Tweeters in G1:

Top Tweeters in G2:

Top Tweeters in G3:

@covestro | ||

@kiri_industries | ||

@h2gazette | ||

@huntsman_corp | ||

@archromagroup | ||

@hydrogenfsummit | ||

@diccorporation | ||

@chemicalupdates | ||

@chemicalsgreen | ||

@ecochemindia | ||

Top Tweeters in G1:

@covestro | ||

@kiri_industries | ||

@huntsman_corp | ||

@archromagroup | ||

@diccorporation | ||

@chemicalupdates | ||

Top Tweeters in G2:

@h2gazette | ||

@hydrogenfsummit | ||

@energyestate | ||

Top Tweeters in G3:

@chemicalsgreen | ||

@ecochemindia | ||