相互伝播モデル

English translation: diffusion model (with interaction effects)

GLOSSARY ENTRY (DERIVED FROM QUESTION BELOW)
Japanese term or phrase:相互伝播モデル
English translation:diffusion model (with interaction effects)
Entered by: DLyons

03:28 Feb 2, 2015
Japanese to English translations [PRO]
Science - Mathematics & Statistics
Japanese term or phrase: 相互伝播モデル
Hi everyone,

The title of a paper I'm translating is 実世界の人の数と仮想世界のツイート数の相互伝播モデルの提案. The model describes the influence of the number of tweets on the number of people in a certain location. Literally translated we have "Mutual Spread Model", or "Mutual Transmission Model," but it feels wrong and such models don't seem to exist. I want to translate this as "Mutual Influence Model," but I was wondering if these seems okay or if anyone has a better term that could be used. The model simply uses statistical formulas to express how to two factors influence each other.

Thanks a lot,

Nick
Nicholas Hallsworth
Japan
Local time: 17:42
diffusion model (with interaction effects)
Explanation:
More context is needed describing the proposed model. It sounds a little like "This paper shows that these two tasks can be addressed simultaneously with a probabilistic model involving a mixture of mutually exciting point processes" but there are many other possibilities.

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Note added at 5 hrs (2015-02-02 09:09:42 GMT)
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"A (lagged) community influence model" seems to capture the key idea. You might find "spatial influence" or even "community-spatial influence" appropriate also. See

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.361...
for ideas!

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Note added at 5 hrs (2015-02-02 09:21:47 GMT)
--------------------------------------------------

"Spatio/Temporal Graphical Models" are also worth considering. "Temporal" is a more usual term in this context than my "lagged".

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Note added at 5 hrs (2015-02-02 09:24:25 GMT)
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"A Spatio/Temporal graphical model for the mutual interaction of agent numbers and location references" seems like a suitably inscrutable title :-)
Selected response from:

DLyons
Ireland
Local time: 08:42
Grading comment
Thanks for all your help!
4 KudoZ points were awarded for this answer



Summary of answers provided
3 +2diffusion model (with interaction effects)
DLyons
4reciprocal propagation influence model
Vladyslav Golovaty
3dissemination model of the mutual effects of A and B
hige
1reciprocal influence model
V N Ganesh


Discussion entries: 2





  

Answers


1 hr   confidence: Answerer confidence 1/5Answerer confidence 1/5
reciprocal influence model


Explanation:
Personality development at school: Assessing a reciprocal influence model ... discussed with reference to transactional models of personality change. .... P as being aligned to tendencies that can best be described ..
www.researchgate.net/...reciprocal_influence_model.../

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Note added at 1 hr (2015-02-02 04:47:27 GMT)
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mutual influence model

However, in the mutual-influence model, the outcomes for the two people directly influence one another: There is reciprocal causation or feedback. For instance ...
https://books.google.co.in/books?isbn=1572309865

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Note added at 3 hrs (2015-02-02 06:46:27 GMT)
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I think the statistical term 'correlation' can be used instead of 'mutual influence', when there is no direct relationship.Pl.wait for a better answer.

Ref. for correlation coefficient:https://books.google.co.in/books?isbn=1118893174

V N Ganesh
Local time: 14:12
Specializes in field
Native speaker of: English
PRO pts in category: 27
Notes to answerer
Asker: Thank you for your answer. In the model I'm translating, the two factors (no. of tweets and no. of people) influence each other statistically, but not directly because we cannot assume the the people posting the tweets are the same people visiting the location. Would this still be a mutual influence model, even thought the influence is not "direct" as such?

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5 hrs   confidence: Answerer confidence 3/5Answerer confidence 3/5 peer agreement (net): +2
diffusion model (with interaction effects)


Explanation:
More context is needed describing the proposed model. It sounds a little like "This paper shows that these two tasks can be addressed simultaneously with a probabilistic model involving a mixture of mutually exciting point processes" but there are many other possibilities.

--------------------------------------------------
Note added at 5 hrs (2015-02-02 09:09:42 GMT)
--------------------------------------------------

"A (lagged) community influence model" seems to capture the key idea. You might find "spatial influence" or even "community-spatial influence" appropriate also. See

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.361...
for ideas!

--------------------------------------------------
Note added at 5 hrs (2015-02-02 09:21:47 GMT)
--------------------------------------------------

"Spatio/Temporal Graphical Models" are also worth considering. "Temporal" is a more usual term in this context than my "lagged".

--------------------------------------------------
Note added at 5 hrs (2015-02-02 09:24:25 GMT)
--------------------------------------------------

"A Spatio/Temporal graphical model for the mutual interaction of agent numbers and location references" seems like a suitably inscrutable title :-)


    Reference: http://www.cc.gatech.edu/~zha/papers/Hawkes-14.pdf
DLyons
Ireland
Local time: 08:42
Specializes in field
Native speaker of: English
PRO pts in category: 24
Grading comment
Thanks for all your help!
Notes to answerer
Asker: Thank you for your response! I will describe the proposed model in a bit more detail. The model consists of nodes and weighted links connecting the nodes. There are two variables, the number of people in a certain location in Tokyo and the number of tweets containing the name of that location each measured in a time series every 15 minutes over two months. The model expresses the influence of each value on the other value for each time step and the previous one time step, for example the strength of the influence of the number of tweets on the number of people and vice versa. It captures the statistical relationship between tweets in virtual space and people in real space. It looks at the peaks where each variable is influencing the other throughout different times of the day. However, the author states that, although there is strong statistical correlation, a direct relationship cannot be inferred because we don't know that the people posting the tweets are the same people in the location. Hope that helps!


Peer comments on this answer (and responses from the answerer)
agree  Takeshi MIYAHARA: Based on searches, I believe every suggestion seems to go fine with this term, but then voting would be a help to choose one from these all nice suggestions :) http://hrcak.srce.hr/file/28748
5 hrs
  -> Thanks Takeshi. Interesting reference.

agree  Yasutomo Kanazawa
2 days 23 hrs
  -> Thanks Yasutomo.
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8 hrs   confidence: Answerer confidence 3/5Answerer confidence 3/5
dissemination model of the mutual effects of A and B


Explanation:
I think mutual relationship (相互関係)or mutual effect (相互作用) is suitable. Other possibilities include:
Dissemination model of the interaction between A and B.
(of could be replaced with 'showing')
Dissemination model showing the interaction between A and B.
Do you think any of these would fit?

hige
Japan
Native speaker of: Native in EnglishEnglish
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8 hrs   confidence: Answerer confidence 4/5Answerer confidence 4/5
reciprocal propagation influence model


Explanation:
it's just an explanation of what model they have built
it's not a specialized type of model used which is easily googled
IMHO

Example sentence(s):
  • a novel propagation model that generalizes the classic Independent ... to detect a set of communities and their reciprocal influence strength.
  • Influence of a forest edge on acoustical propagation: experimental results. ... effects are not sufficient to explain the apparent non-reciprocal propagation.

    Reference: http://link.springer.com/chapter/10.1007%2F978-3-642-40991-2...
    Reference: http://www.ncbi.nlm.nih.gov/pubmed/23654365
Vladyslav Golovaty
Ukraine
Local time: 10:42
Native speaker of: Native in EnglishEnglish, Native in RussianRussian
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