Example of Discourse Processes format
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Example of Discourse Processes format Example of Discourse Processes format Example of Discourse Processes format Example of Discourse Processes format Example of Discourse Processes format Example of Discourse Processes format
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Example of Discourse Processes format Example of Discourse Processes format Example of Discourse Processes format Example of Discourse Processes format Example of Discourse Processes format Example of Discourse Processes format
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This content is only for preview purposes. The original open access content can be found here.
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Discourse Processes — Template for authors

Publisher: Taylor and Francis
Categories Rank Trend in last 3 yrs
Language and Linguistics #49 of 879 down down by 16 ranks
Linguistics and Language #56 of 935 down down by 18 ranks
Communication #59 of 426 down down by 32 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 178 Published Papers | 595 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 06/07/2020
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SJR: 0.766
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Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

1.612

2% from 2018

Impact factor for Discourse Processes from 2016 - 2019
Year Value
2019 1.612
2018 1.58
2017 1.789
2016 2.074
graph view Graph view
table view Table view

3.3

3% from 2019

CiteRatio for Discourse Processes from 2016 - 2020
Year Value
2020 3.3
2019 3.4
2018 3.3
2017 3.4
2016 2.9
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 2% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has decreased by 3% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

0.947

4% from 2019

SJR for Discourse Processes from 2016 - 2020
Year Value
2020 0.947
2019 0.988
2018 0.906
2017 0.989
2016 1.274
graph view Graph view
table view Table view

1.603

17% from 2019

SNIP for Discourse Processes from 2016 - 2020
Year Value
2020 1.603
2019 1.371
2018 1.14
2017 1.23
2016 1.319
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 4% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 17% in last years.
  • This journal’s SNIP is in the top 10 percentile category.
Discourse Processes

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Taylor and Francis

Discourse Processes

Discourse Processes is a multidisciplinary journal providing a forum for cross-fertilization of ideas from diverse disciplines sharing a common interest in discourse--prose comprehension and recall, dialogue analysis, text grammar construction, computer simulation of natural l...... Read More

Language and Linguistics

Linguistics and Language

Communication

Arts and Humanities

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Last updated on
06 Jul 2020
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ISSN
0163-853X
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Impact Factor
High - 1.199
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Open Access
No
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Sherpa RoMEO Archiving Policy
Green faq
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Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Bibliography Name
Taylor and Francis Custom Citation
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Citation Type
Numbered
[25]
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Bibliography Example
Blonder GE, Tinkham M, Klapwijk TM. Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion. Phys Rev B. 1982; 25(7):4515–4532. Available from: 10.1103/PhysRevB.25.4515.

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1080/01638539809545028
An introduction to latent semantic analysis
Thomas K. Landauer1, Peter W. Foltz2, Darrell Laham1
01 Jan 1998 - Discourse Processes

Abstract:

Latent Semantic Analysis (LSA) is a theory and method for extracting and representing the contextual‐usage meaning of words by statistical computations applied to a large corpus of text (Landauer & Dumais, 1997). The underlying idea is that the aggregate of all the word contexts in which a given word does and does not appear ... Latent Semantic Analysis (LSA) is a theory and method for extracting and representing the contextual‐usage meaning of words by statistical computations applied to a large corpus of text (Landauer & Dumais, 1997). The underlying idea is that the aggregate of all the word contexts in which a given word does and does not appear provides a set of mutual constraints that largely determines the similarity of meaning of words and sets of words to each other. The adequacy of LSA's reflection of human knowledge has been established in a variety of ways. For example, its scores overlap those of humans on standard vocabulary and subject matter tests; it mimics human word sorting and category judgments; it simulates word‐word and passage‐word lexical priming data; and, as reported in 3 following articles in this issue, it accurately estimates passage coherence, learnability of passages by individual students, and the quality and quantity of knowledge contained in an essay. read more read less

Topics:

Latent semantic analysis (61%)61% related to the paper, Probabilistic latent semantic analysis (58%)58% related to the paper, Vocabulary (54%)54% related to the paper, Similarity (psychology) (53%)53% related to the paper, Semantics (53%)53% related to the paper
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4,391 Citations
Journal Article DOI: 10.1080/01638539809545029
The Measurement of Textual Coherence with Latent Semantic Analysis.
Peter W. Foltz1, Walter Kintsch2, Thomas K. Landauer2
01 Jan 1998 - Discourse Processes

Abstract:

Latent Semantic Analysis (LSA) is used as a technique for measuring the coherence of texts. By comparing the vectors for 2 adjoining segments of text in a high‐dimensional semantic space, the method provides a characterization of the degree of semantic relatedness between the segments. We illustrate the approach for predictin... Latent Semantic Analysis (LSA) is used as a technique for measuring the coherence of texts. By comparing the vectors for 2 adjoining segments of text in a high‐dimensional semantic space, the method provides a characterization of the degree of semantic relatedness between the segments. We illustrate the approach for predicting coherence through reanalyzing sets of texts from 2 studies that manipulated the coherence of texts and assessed readers’ comprehension. The results indicate that the method is able to predict the effect of text coherence on comprehension and is more effective than simple term‐term overlap measures. In this manner, LSA can be applied as an automated method that produces coherence predictions similar to propositional modeling. We describe additional studies investigating the application of LSA to analyzing discourse structure and examine the potential of LSA as a psychological model of coherence effects in text comprehension. read more read less

Topics:

Coherence (statistics) (66%)66% related to the paper, Probabilistic latent semantic analysis (59%)59% related to the paper, Semantic similarity (56%)56% related to the paper, Latent semantic analysis (56%)56% related to the paper
776 Citations
Journal Article DOI: 10.1207/S15326950DP3802_5
Transportation Into Narrative Worlds: The Role of Prior Knowledge and Perceived Realism.
Melanie C. Green1
01 Sep 2004 - Discourse Processes

Abstract:

"Transportation into a narrative world" (Green & Brock, 2000, 2002) has been identified as a mechanism of narrative impact. A transported individual is cognitively and emotionally involved in the story and may experience vivid mental images. In the study reported here, undergraduate participants (N = 152) read a narrative abo... "Transportation into a narrative world" (Green & Brock, 2000, 2002) has been identified as a mechanism of narrative impact. A transported individual is cognitively and emotionally involved in the story and may experience vivid mental images. In the study reported here, undergraduate participants (N = 152) read a narrative about a homosexual man attending his college fraternity reunion, rated their transportation into the story, rated the perceived realism of the story, and responded to statements describing story-relevant beliefs. Transportation was positively correlated with perceived realism. Furthermore, individuals with prior knowledge or experience relevant to the themes of the story (e.g., had homosexual friends or family members, were knowledgeable about American fraternities) showed greater transportation into the story. Highly transported readers showed more story-consistent beliefs, and the positive relationship between transportation and story-consistent beliefs held for those both with and wit... read more read less

Topics:

Narrative (56%)56% related to the paper
723 Citations
Journal Article DOI: 10.1080/01638539609544975
Learning from texts: Effects of prior knowledge and text coherence
Danielle S. McNamara1, Walter Kintsch2
01 Oct 1996 - Discourse Processes

Abstract:

Two experiments, theoretically motivated by the construction‐integration model of comprehension (W. Kintsch, 1988), investigated effects of prior knowledge on learning from high‐ and low‐coherence history texts. In Experiment 1, participants’ comprehension was examined through free recall, multiple‐choice questions, and a key... Two experiments, theoretically motivated by the construction‐integration model of comprehension (W. Kintsch, 1988), investigated effects of prior knowledge on learning from high‐ and low‐coherence history texts. In Experiment 1, participants’ comprehension was examined through free recall, multiple‐choice questions, and a keyword sorting task. An advantage was found for the high‐coherence text on recall and multiple‐choice questions. However, high‐knowledge readers performed better on the sorting task after reading the low‐coherence text. In Experiment 2, participants’ comprehension was examined through open‐ended questions and the sorting task both immediately and after a 1‐week delay. Little effect of delay was found, and the previous sorting task results failed to replicate. As predicted, high‐knowledge readers performed better on the open‐ended questions after reading the low‐coherence text. Reading times from both experiments indicated that the low‐coherence text requires more inference processes. Th... read more read less

Topics:

Reading comprehension (56%)56% related to the paper, Free recall (56%)56% related to the paper, Reading (process) (54%)54% related to the paper, Comprehension (50%)50% related to the paper
708 Citations
Journal Article DOI: 10.1080/01638530802073712
Gender Differences in Language Use: An Analysis of 14,000 Text Samples
Matthew L. Newman1, Carla J. Groom2, Carla J. Groom3, Lori D. Handelman4, James W. Pennebaker
13 Jun 2008 - Discourse Processes

Abstract:

Differences in the ways that men and women use language have long been of interest in the study of discourse. Despite extensive theorizing, actual empirical investigations have yet to converge on a coherent picture of gender differences in language. A significant reason is the lack of agreement over the best way to analyze la... Differences in the ways that men and women use language have long been of interest in the study of discourse. Despite extensive theorizing, actual empirical investigations have yet to converge on a coherent picture of gender differences in language. A significant reason is the lack of agreement over the best way to analyze language. In this research, gender differences in language use were examined using standardized categories to analyze a database of over 14,000 text files from 70 separate studies. Women used more words related to psychological and social processes. Men referred more to object properties and impersonal topics. Although these effects were largely consistent across different contexts, the pattern of variation suggests that gender differences are larger on tasks that place fewer constraints on language use. read more read less

Topics:

Written language (59%)59% related to the paper, Sociolinguistics (56%)56% related to the paper, Variation (linguistics) (55%)55% related to the paper, Discourse analysis (51%)51% related to the paper, On Language (51%)51% related to the paper
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630 Citations
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Frequently asked questions

1. Can I write Discourse Processes in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Discourse Processes guidelines and auto format it.

2. Do you follow the Discourse Processes guidelines?

Yes, the template is compliant with the Discourse Processes guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Discourse Processes?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Discourse Processes citation style.

4. Can I use the Discourse Processes templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Discourse Processes.

5. Can I use a manuscript in Discourse Processes that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Discourse Processes that you can download at the end.

6. How long does it usually take you to format my papers in Discourse Processes?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Discourse Processes.

7. Where can I find the template for the Discourse Processes?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Discourse Processes's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the Discourse Processes's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. Discourse Processes an online tool or is there a desktop version?

SciSpace's Discourse Processes is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Discourse Processes?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Discourse Processes?”

11. What is the output that I would get after using Discourse Processes?

After writing your paper autoformatting in Discourse Processes, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Discourse Processes's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Discourse Processes?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Discourse Processes. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Discourse Processes?

The 5 most common citation types in order of usage for Discourse Processes are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Discourse Processes?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Discourse Processes's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Discourse Processes in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Discourse Processes Endnote style according to Elsevier guidelines.

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I spent hours with MS word for reformatting. It was frustrating - plain and simple. With SciSpace, I can draft my manuscripts and once it is finished I can just submit. In case, I have to submit to another journal it is really just a button click instead of an afternoon of reformatting.

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