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#iconohash presents #phdchat

Scroll down for the #phdchat conversation report for November 20th, 2020 EST.

iconohash

the world's conversation archive

#phdchat for November 20th, 2020 EST

01
2nd

coming together

When it comes to participants, we ranked 2nd among 184 conversations.

2nd

participating

In terms of the number of posts, we ranked 2nd out of 184 conversations that took place.

1st

amplification

This conversation ranked 1st out of 184 in terms of the amplification of ideas & content.

how we participated. Here's how participants reacted & engaged each other

Reactions
74%

Amplified

There were 248 reshares, 74% of posts, during the course of the conversation.

1%

Engaged

1% of participants in this conversation engaged each other 2 times.

18%

Content

18% of participants in this conversation shared a total of 11 unique pieces of content.

quick facts.

Here are the basic facts of the conversation for for November 20th, 2020.

0
Active
Participants
0
Posts
Total

meet the influencers the movers and shakers of #phdchat

02

the top of the list. Top influencers in the chat

IMPACT
@OpenAcademics

@OpenAcademics

OpenAcademics
Twitter community to support fellow academics across all disciplines. @OpenAcademics for RT. #DiversityandInclusion #MentalHealth #OAposter

@joanneXaugust

@joanneXaugust

Joanne August
bibliophile unicorn

@nicolasaguilar

@nicolasaguilar

Nicolas Aguilar
Physical activity and public policies for promoting health equity and access are my main interests. #UFRO #ActividadFisica #donante

about the participants. let's take a look at everyone who show'd up

03

top professions what are they doing when they're not in #phdchat

insight

  the top participating professions
out of 43 total

research
training
writing
educator
professor

gender an estimation of what the gender break down looks like
= 1 men or women

insight

Women

Men

about the content. the best content that was shared

04
Plants | Free Full-Text | Comparison of Read Mapping and Variant Calling Tools for the Analysis of Plant NGS Data
High-throughput sequencing technologies have rapidly developed during the past years and have become an essential tool in plant sciences. However, the analysis of genomic data remains challenging and relies mostly on the performance of automatic pipelines. Frequently applied pipelines involve the alignment of sequence reads against a reference sequence and the identification of sequence variants. Since most benchmarking studies of bioinformatics tools for this purpose have been conducted on huma

chat growth how is #phdchat growing over time?

05

want more? are you interested in the full data analysis for this chat? Full transcript? Longer view at chat growth?

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