=Paper=
{{Paper
|id=Vol-2342/paper9
|storemode=property
|title=Towards the Automatic Analysis of the Structure of News Stories
|pdfUrl=https://ceur-ws.org/Vol-2342/paper9.pdf
|volume=Vol-2342
|authors=Iqra Zahid,Hao Zhang,Frank Boons,Riza Batista-Navarro
|dblpUrl=https://dblp.org/rec/conf/ecir/ZahidZBB19
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==Towards the Automatic Analysis of the Structure of News Stories==
https://ceur-ws.org/Vol-2342/paper9.pdf
Towards the Automatic Analysis
of the Structure of News Stories
Iqra Zahid Hao Zhang
School of Arts, Languages and Cultures School of Computer Science
University of Manchester, UK University of Manchester, UK
iqra.zahid@student.manchester.ac.uk hao.zhang-17@postgrad.manchester.ac.uk
Frank Boons Riza Batista-Navarro
Alliance Manchester Business School School of Computer Science
University of Manchester, UK University of Manchester, UK
frank.boons@manchester.ac.uk riza.batista@manchester.ac.uk
Abstract
News stories are distinct from other types of narratives in that they
typically follow a complex and non-chronological time structure. This
poses challenges to the narrative analysis of news, specifically with re-
spect to the construction of event sequences. In this paper, we propose
to segment news story text according to news schema categories, which
allow for identifying sentences describing a news story’s main action
and other actions that happened beforehand or subsequently. To au-
tomate this task, we made observations on the linguistic devices that
are used by news writers, based on a manually annotated corpus of
news articles that we have constructed. Heuristics capturing these lin-
guistic devices were then developed, underpinned by natural language
processing tools as well as carefully curated look-up lists of cues. While
encouraging preliminary results were obtained, the work can be further
expanded by observing and capturing more linguistic devices, which
can be facilitated by further annotation of news stories based on news
schema categories.
1 Introduction
In analysing narratives, understanding the sequence in which events occur is key [Ell05]. Most types of narratives,
e.g., novels, personal accounts of experiences, present events in chronological order. However, news stories,
narratives that are written or recorded to “inform the public about current events, concerns or ideas” [Whi],
deviate from other types of narratives in that they follow a complex time structure. News writers are expected
to prioritise certain news values, i.e., criteria for judging “newsworthiness” (e.g., negativity, unexpectedness,
superlativeness) [Bel91]. In producing news stories that adhere to such news values, news writers adopt the
Copyright c 2019 for the individual papers by the paper’s authors. Copying permitted for private and academic purposes. This
volume is published and copyrighted by its editors.
In: A. Jorge, R. Campos, A. Jatowt, S. Bhatia (eds.): Proceedings of the Text2StoryIR’19 Workshop, Cologne, Germany, 14-April-
2019, published at http://ceur-ws.org
Figure 1: News schema proposed by Allan Bell [Bel91]. Shown in grey are the most specific categories in the
schema.
instalment method, whereby an event that was introduced in the earlier parts of a story, may be described
in detail only later on in the story, possibly in multiple, separate instances. Consequently, events are usually
presented in news stories in a non-chronological order.
In order to understand the flow of events in news stories, it is necessary to analyse their schema, i.e., the
overall form of news discourse, by which topics are organised. A news schema defines the syntax of news
stories, providing a set of formal categories that form the basis of the hierarchical organisation and ordering of
textual units [Dij85]. In early work by Labov and Waletzky on discourse analysis, categories such as Abstract,
Orientation, Complicating Action, Evaluation, Resolution and Coda were proposed in order to organise narratives
of personal experiences [LW67]. Building upon that work, van Dijk [Dij85] developed a schema specifically for
analysing news discourse. Each category in the schema, e.g., Main Event, Background and History, corresponds
to a piece of text, i.e., a sequence of sentences. According to case studies carried out on hundreds of news reports
published in more than 260 newspapers from 100 countries, this news schema is applicable at an international
scale [vD98]. A few years later, building upon van Dijk’s work, Bell proposed a finer-grained news schema
[Bel91]. We reproduce a tree-like depiction of this schema in Figure 1, in which the most specific (or lowest-level)
categories are shown in grey.
Since the chronological order of events is not maintained in news stories (as discussed above), narrative analysis
of news is more challenging, compared to that of other types of narratives (e.g., novels). As human readers, we
are accustomed to the style of reporting employed in news stories, and thus we might find the task of determining
the correct sequence of events a simple and straightforward task. However, to an automated system designed to
support narrative analysis, the non-chronological order in which events are presented in news stories would pose
a barrier in the reconstruction of event sequences.
In this paper, we aim to facilitate machine understanding of news stories by automatically decomposing them
according to news schema categories. To this end, we firstly developed a corpus of written news stories in which
spans of text corresponding to news schema categories have been manually annotated and labelled following the
work of Bell [Bel91]. We then identified the various linguistic devices that are usually employed by news writers,
that can help in the task of mapping news story text, to respective news schema categories. On the basis of
these, a heuristics-based approach was developed in order to automate the said task.
The remainder of this paper is organised as follows. Section 2 presents a review of previously reported related
work. In Section 3, an analysis of linguistic devices used in the different news schema categories is presented,
supported by an annotated corpus that we have recently developed. We also provide a discussion of the heuristics
that were developed to detect the use of such linguistic devices, in order to identify parts of news story text that
correspond to schema categories. Our preliminary results are then discussed in Section 4. Finally, we conclude
and present our next steps in Section 5.
2 Related Work
Most of the efforts that have been carried out in the way of analysing news were focussed on identifying boundaries
between news stories, rather than on analysing their structure individually. Early work employed cue words as
well as named entities (e.g., names of people, places, organisations) in closed caption text, in order to detect
transitions from one news story to another [MMM97]. The Broadcast News Navigator (BNN) system similarly
used cue words and named entities in segmenting closed caption text according to individual news stories [May98].
Additionally, by selecting the sentence with the highest frequency of named entities, the system was able to
generate a gist for each news story—slightly similar to the Action category in Bell’s framework which pertains
to the central or main action in a news story.
TextTiling, a text segmentation approach proposed by Hearst, was applied to the detection of boundaries
between consecutive news articles in the Wall Street Journal [Hea97]. Specifically, the approach segmented text
according to subtopics, which were identified through the measurement of lexical cohesion. Other work sought
to improve the definition and measurement of lexical cohesion, by incorporating richer features (e.g., number of
pronouns, similarities obtained by Latent Dirichlet Allocation), and were applied to the detection of news story
boundaries in transcripts of broadcast news [Sto03, RH06, PMD09].
More similar to our own work are efforts aimed at segmenting individual narratives. The work of Kauchak
and Chen [KC05] was aimed at segmenting an individual narrative according to the topics it contains, casting
the problem as a text classification task in which features such as word groups (identified with the aid of
WordNet) and entity groups were learned using machine learning-based methods, i.e., support vector machines
and decision stumps (one-level decision trees). This approach was applied on books autobiography-style books
and encyclopaedia articles. Our approach is distinct from this in that we seek to segment individual news stories,
which as discussed in the previous section, follow a different structure relative to other types of narratives.
While the work of Cardoso et al. [CTP13] was targeted towards the analysis of news text (written in Brazilian
Portuguese), they also used topics as the basis of segmentation.
Our work aims to segment a narrative with the end-goal of following the flow or sequence of events, rather
than identifying the different topics or themes it contains. While this bears similarities with the narrative
segment annotation task proposed by Reiter [Rei15] which was manually applied to short stories, our approach
is specifically aimed at automatically analysing news stories. The topic of a news story may consist of multiple
interconnected events, and thus can be segmented according to news schema categories delineating the main
event from events leading to it and following it. To the best of our knowledge, our proposed approach is the first
to attempt to automatically analyse the structure of news stories in this way.
3 Methodology
Our proposed approach to the automatic segmentation of news text according to news schema categories is based
on the analysis of the various linguistic devices used by writers.
3.1 Corpus development
In order to support our analysis of linguistic devices, we developed a small corpus of written news articles,
retrieved using the LexisNexis library1 . Containing a total of 22 articles from various news agencies (listed in
Appendix A), the corpus is partitioned into two: (1) a pre-2005 set, mostly containing news stories published
in the 1980s and 1990s, that were used by van Dijk [Dij85, vD98] and Bell [Bel91] in designing their respective
frameworks; and (2) a post-2005 set, containing eight news stories published more recently.
An annotation scheme was designed requiring annotators to map pieces of news text to the most specific
categories of the news schema tree (shown in grey in Figure 1). Guidelines were then established, to promote
consistency between annotators. Specifically, annotators were asked to provide annotations at the sentence level.
That is, category labels were assigned to individual sentences, not to whole paragraphs (sequence of sentences)
nor to clauses or phrases (parts of sentences). If a sequence of sentences corresponds to only one category, then
1 https://www.lexisnexis.com/uk/legal/
Figure 2: News story “Students Defiant as Chinese University Cracks Down on Young Communists” (Javier
C.Hernandez, The New York Times, 28 December 2018) annotated and visualised using the brat annotation
tool.
each sentence in that sequence was labelled as that one category. On each sentence, only one of eight of the most
specific news schema categories (Action, Reaction, Consequence, Context, Evaluation, Expectation, Previous
episode, History) was applied. We refer the reader to Appendix B for the definitions of these categories, as well
as corresponding example sentences coming from a news story. Annotators were encouraged to firstly identify
sentences in a news story that pertain to Action, as the other seven news schema categories are defined in relation
to it. In cases where a sentence seemed to map to multiple categories, the annotator was asked to choose only
one based on his or her best judgement.
Using the brat rapid annotation tool [SPT+ 12], two annotators carried out the annotation task. One an-
notator, a final-year linguistics student (the first author of this paper), marked up all of the 22 articles. The
other annotator, a researcher with expertise in natural language processing and text mining (the last author),
annotated only the post-2005 set. Shown in Figure 2 is a sample news story annotated and visualised in brat.
The resulting corpus contains a total of 570 sentences. The average number of sentences is 26, with the
shortest and longest news stories containing 11 and 53 sentences, respectively. Shown in Figure 3 is the number
of annotated sentences in the corpus for each news schema category.
Figure 3: Number of sentences in the annotated corpus, for each news schema category.
3.2 Linguistic Devices
Utilising our manually annotated corpus, we made observations on the various linguistic devices used by news
story writers, as we posit that these are helpful in discriminating between different news schema categories.
These observations are discussed for each of the eight most specific news schema categories, together with our
proposed heuristics for automatically capturing them.
3.2.1 Action.
We observed that sentences pertaining to Action, defined as a central or main action in a news story, share
lexical similarities with the title of the news story. For example, in the news article published by the BBC
News on the 21st December 2018 entitled, “Cheshire BMW driver jailed over speeding ticket lie”, the following
sentences pertain to Action: (1) “A man who claimed his BMW had been cloned as part of an elaborate scam
to avoid a speeding fine has been jailed.”; and (2) “Robson was jailed for nine months at Chester Crown Court
on Thursday.” Words in these sentences such as “jailed” and “speeding” are shared (verbatim) with the title of
the news story. Based on this observation, we automatically identified text pertaining to Action by checking for
exact matches between the lemmatised words of a sentence and those of the news story title.
3.2.2 Reaction.
A Reaction is a verbal response to an Action given by an actor. A commonly used linguistic device used by
writers to describe Reactions is attribution, which indicates “who expressed what”, where what pertains to a
quotation or perception, and “who” denotes its original source, i.e., the actor. The information that is commonly
attributed is direct speech (e.g., He said, “She will deny it.”) or indirect speech (e.g., He said that she will deny
it.) in which reporting verbs (e.g., “said”, “announce”, “comment”, “mention”) are often used. However, verbs
that are less neutral and bear either positive or negative connotations may also be used, such as “applaud”,
“praise” and “complain”.
To detect whether a sentence contains a Reaction, we leveraged previously reported work on attribution
extraction, which is underpinned by a lexicon of attribution verbs [ZBBNss]. As Reactions are responses to
Actions, they often contain mentions that co-refer to either the Action itself or actors participating in it. Hence,
a check for the use of definite noun phrases was also implemented in order to detect whether an attributed
quotation contains any co-referring mentions.
3.2.3 Consequence.
A Consequence is an occurrence that transpires as a result of an Action, with the exception of verbal responses
(which are classified as Reactions). As such, Consequences often contain mentions that co-refer to either the
Action itself or actors participating in it. Furthermore, discourse connectives signifying causation (e.g., “as a
result”, “because”, “thereby”) tend to be used in sentences pertaining to Consequence. In order to detect the
use of such linguistic devices, we checked for the existence of definite noun phrases in sentences, as well as for
the use of any of the discourse connectives annotated in the Penn Discourse Treebank (PDTB) [PDL+ 08] that
denote the Contingency relation (with a minimum frequency = 4).
3.2.4 Evaluation.
Evaluation consists of observations on an Action provided by the news writer (i.e., journalist) or an actor, that
assesses its impact or significance. As in Reaction, attribution is often used in Evaluation, specifically in cases
where the observations are coming from actors. However, sentences conveying Evaluation can be identified by
checking for the presence of graded adjectives, as these often indicate assessment, i.e., the degree to which a
quality holds (e.g., “deep”, “strongest”, “biggest”). In support of this step, more than 260 graded adjectives
were collected from the Collins Cobuild Grammar Patterns reference book [Sin98] and compiled into a look-up
list.
3.2.5 Expectation.
Like Evaluation, Expectation is comprised of observations provided by the news writer or an actor (in which
case attribution is also used), but pertains to their views on what could happen in the future. As such, sentences
corresponding to Expectation make use of speculative language. To facilitate the detection of speculative lan-
guage, we checked for the presence of modal verbs (e.g., “could”, “may”), as well as for presence of modifiers that
indicate uncertainty. A list of such modifiers was drawn from uncertainty cues in the WikiWeasel 2.0 corpus,
that were manually annotated by Vincze [Vin14].
3.2.6 Context.
Similar to Evaluation and Expectation, Context refers to observations given by either the news writer or an actor
in order to provide additional information that help explain or clarify details surrounding an Action. Based on
our observations, sentences that fall under this category do not have any defining linguistic features (unlike
Evaluation and Expectation as described above), except for the prevalent use of co-referring mentions. We
detected this by checking if definite noun phrases appear as either the subject or object of sentences.
3.2.7 Previous episode.
Sentences pertain to a Previous episode if they describe any event that happened prior to an Action, in the
not-so-distant (or near) past. The main verbs of such sentences are often in either the past or past perfect tense.
Additionally, relative temporal expressions pertaining to recent points in time (e.g., “last week”, “previously”,
“on Friday”) also tend to be used in specifying the time of occurrence of events falling under Previous episode.
3.2.8 History.
Similar to Previous episode, History describes events that happened prior to an Action, but before the near past.
Sentences that belong to this category typically have main verbs in either the past or past perfect tense. They
also describe events whose time of occurrence are mentioned in the form of absolute temporal expressions (e.g.,
“in 1989”). However, relative temporal expressions may also be used, although these would pertain to a point
in time from the distant past (e.g., “three decades ago”).
4 Preliminary Results
In implementing the heuristics for capturing linguistic devices that were discussed in the previous section, a
pipeline for preprocessing was developed, based on three tools. Firstly, we made use of the LingPipe sentence
splitter2 , to automatically segment news text into individual sentences. Each sentence is then decomposed into
tokens by the GENIA Tagger3 . The tokenised sentence is then given as input to the Enju Parser4 , through
which we obtained not only the part-of-speech (POS) tag and lemma for each token but also predicate-argument
structures identifying the sentence’s main verb and its arguments (i.e., subject and object).
We then developed (in Python) rules for analysing the preprocessing results, for each news schema category
(as described in the previous section). These include: (1) checking for specific values of POS tags, e.g., to check
for verb tense and for modal verbs; (2) matching lemmatised tokens in look-up lists, e.g., of uncertainty cues,
graded adjectives; (3) checking for definite noun phrases and whether they act as the subject or object of a
main verb; and (4) matching against regular expressions designed to capture absolute and relative temporal
expressions.
Upon application on the post-2005 set of our annotated corpus (containing eight news stories), our heuristics
for identifying sentences obtained an overall performance of 64% (over all eight news schema categories) in terms
of F-score (precision = 70%, recall = 59%).
5 Future Work and Conclusion
In this paper, we presented our work on automatically analysing the structure of news stories according to news
schema categories. While our preliminary results are encouraging, there is significant room for improvement.
Recognising that the current version of our annotated corpus is limited in size, we shall a dedicate a large
part of our immediate next step on expanding it. This will allow us to observe any further linguistic devices
used in each news schema category, and in turn, to eventually extend our heuristics. Our annotated corpus
will be made publicly available upon completion of this planned expansion. We then intend to investigate how
2 http://alias-i.com/lingpipe/index.html
3 http://www.nactem.ac.uk/GENIA/tagger/
4 http://www.nactem.ac.uk/enju/
our automatically assigned news schema categories can be used as features to inform event temporal relation
extraction, in the way of automatically constructing event sequences.
5.0.1 Acknowledgements
The research on which this article is based was partially funded by the Alliance Manchester Business School
Strategic Investment Fund.
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Appendix
A. News articles in the annotated corpus
Date News agency Title
27 Aug 1979 BBC News Soldiers die in Warrenpoint massacre
01 Mar 1982 Newsweek GUATEMALA: NO CHOICES
15 Sept 1982 Bangkok Post ISRAELIS RETURN TO WEST BEIRUT
15 Sept 1982 The New York Times GEMAYEL OF LEBANON IS KILLED IN BOMB BLAST
AT PARTY OFFICES
12 July 1984 International Herald Tribune Lebanese Committee Named to Secure Release of Moslem,
Christian Hostages
12 July 1984 The Times SHULTZ JOINS CRITICS OF INDONESIAN RULE
05 Dec 1984 International Herald Tribune U.S.-Backed Coalition Wins Grenada Election
05 Dec 1984 The Guardian London Reagan favourite sweeps Grenada
05 Dec 1984 The Guardian Blaize the American way
01 Apr 1990 Dominion Sunday Times Troops take over Lithuanian office
02 Apr 1990 The Dominion US Troops ambushed in Honduras
20 Nov 1995 BBC News Diana admits adultery in TV interview
06 Feb 1997 BBC News Widow allowed dead husband’s baby
16 Oct 2006 Manchester Evening News BBC move to Salford may be delayed a year
18 Oct 2006 Manchester Evening News Red faces over BBC’s Salford radio blunder
10 Nov 2006 The Bolton News Councils urge BBC to move north
05 Dec 2006 Manchester Evening News BBC boss confident of Salford Quays move
21 Dec 2018 BBC News Cheshire BMW driver jailed over speeding ticket lie
23 Dec 2018 BBC News Shrewsbury Christmas Festival cancelled after one day
23 Dec 2018 BBC News Uppermill death: Men charged with Daniel Hogan murder
28 Dec 2018 The New York Times Students Defiant as Chinese University Cracks Down on Young
Communists
B. Bell’s most specific news schema categories, with examples drawn from “Students Defiant as Chinese
University Cracks Down on Young Communists” by Javier C.Hernandez, The New York Times, 28 December
2018.
Category Definition Example
Action Central or main action More than a dozen students from Peking University in Beijing,
in a rare rebuke of authority, protested Friday on campus to
draw attention to the university’s attempts to punish students
for taking part in the campaign.
Reaction A response to the Action that Peking University officials moved swiftly to contain Friday’s
was expressed verbally, e.g., a protest, holding the students in classrooms and keeping them
direct/indirect quote, speech, through the night for questioning, activists said.
interview
Consequence An action that transpired as The students have put the government in an awkward posi-
a result of the Action, exclud- tion because they are invoking the teachings of Mao, Marx and
ing verbal responses Lenin, which President Xi Jinping has championed, to point
to problems in Chinese society including inequality, corruption
and greed.
Context Additional information that The students are part of a small but tenacious group of young
help explain or clarify details communists using leftist ideology to shine a light on labor
surrounding the Action abuses across China and to call for better protections for the
working class.
Evaluation An assessment of the signifi- The stern reaction by the authorities reflects the party’s deep
cance of the Action anxieties about the young communists and their unusual cam-
paign.
Expectation A view on what could happen Party leaders may be concerned that the 30th anniversary of
after the Action the massacre, coming up in June, could inspire new protests.
Previous Events that happened more The protest on Friday came after Peking University officials
episode recently (in the near past) tried to block a Marxist student group from organizing a cele-
bration for Mao’s 125th birthday.
History Set of events that happened The party has long feared student-led protests, especially since
before the near past the 1989 pro-democracy movement, which had deep student
involvement and was crushed in a bloody crackdown around
Tiananmen Square.