On the algorithmic role of synonyms and keywords in analytics for catastrophic events

Teodorescu, Horia-Nicolai; Bolea, Speranta Cecilia

doi:10.1109/ecai.2016.7861094

Cited by 5 publications

(14 citation statements)

References 17 publications

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“…Yet, our hypothesis was overturned [24], in that at least the most frequently used words obeyed Zipf's law, while words with higher rank confirmed the hypothesis. The results of log-lin representation of the probabilities of the most frequent 8 words, topic seism for Google+ (3), and Twitter (4) are: …”

Section: Zipf 'S Law and The Lexicons Of Posts On Snsmentioning

confidence: 58%

“…The descriptive statistics, including Zipf's law detection, refers to the whole database, on each SN, thus extending the results in [24].…”

Section: Data Collection and Processing Methodsmentioning

confidence: 98%

“…The data collection process was described in [24]; data comprises all posts, including articles and blogs pointed to by messages on Twitter and Google+, during the period March 2015 and March 2016, as detected with queries using the keywords (cutremur OR seism) AND Vrancea, respectively incendiu OR foc.…”

Section: Data Collection and Processing Methodsmentioning

confidence: 99%

“…This means that selecting at random words in a specified language, the law should not apply. We have been interested, see [24], to find if Zipf's law is relevant to the database related to disasters. Our initial hypothesis was that the law would not be valid because of the very restrictive set of words used in such posts, their low rank in the language, and their supposedly almost random choice from the lexicon of the global lexicon of the language.…”

Section: Zipf 'S Law and The Lexicons Of Posts On Snsmentioning

confidence: 99%

“…The general lexicon was studied in [24], and issues related to the use of synonyms in tweets were discussed in [4], [20], and [24].…”

Section: Introductionmentioning

confidence: 99%

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Language Processes and Related Statistics in the Posts Associated to Disasters on Social Networks

Bolea

2016

INT J COMPUT COMMUN

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This paper provides a detailed and long-period statistics of the use of synonyms in posts related to specific events on social networks (SNs), an extended analysis of the correlations of the flows of the synonyms in such posts, a study of the applicability of Zipf's law to posts related to specific events on SNs, and an analysis of the dynamics of the fluxes of synonyms in the posts. The paper also introduces the study of the distances in the phase space for the characterization of the dynamics of the word fluxes on social networks. This article is a partial report on recent research performed for a deeper analysis of social networks and of processes developing on social networks, including used lexicon, dynamics of messages related to a specific type of topic, and relationships of the processes on SNs with external events.

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Section: Zipf 'S Law and The Lexicons Of Posts On Snsmentioning

confidence: 58%

“…The descriptive statistics, including Zipf's law detection, refers to the whole database, on each SN, thus extending the results in [24].…”

Section: Data Collection and Processing Methodsmentioning

confidence: 98%

Section: Data Collection and Processing Methodsmentioning

confidence: 99%

Section: Zipf 'S Law and The Lexicons Of Posts On Snsmentioning

confidence: 99%

“…The general lexicon was studied in [24], and issues related to the use of synonyms in tweets were discussed in [4], [20], and [24].…”

Section: Introductionmentioning